AI agent applications need a database to persist state, handle concurrent requests, and retrieve context while an agent works. Frequent checkpoints and context queries make database latency part of an agent's response time, and the same service usually holds the application's users, permissions, and transactional data.
This guide compares ClickHouse Managed Postgres and Crunchy Bridge across dimensions that matter for AI agent applications: transactional performance, retrieval, agent tooling, and development workflows. It also covers storage and scaling, availability, recovery, pricing, analytics integration, and migration.
TL;DR
Choose ClickHouse Managed Postgres when you need fast transactional throughput on local NVMe, integrated operational tooling, or a path into ClickHouse analytics. The Xata acquisition aims to add scale-to-zero and copy-on-write branching. Choose Crunchy Bridge when you need independent storage sizing, broad PostgreSQL extension support, or multi-cloud deployment.
- Local NVMe gives ClickHouse Managed Postgres a direct storage path. PostgresBench shows substantially higher throughput for ClickHouse at the larger tested configuration and comparable throughput at the smaller one.
- ClickHouse offers asynchronous or synchronous-quorum standbys. Bridge uses a hidden HA standby on eligible plans.
- Both support vector retrieval, pooled connections, APIs, CLIs, and isolated database copies. ClickHouse adds read-only MCP access to PostgreSQL data and diagnostics. Bridge offers configurable pooling modes.
- ClickHouse scales through NVMe instance configurations. Bridge can grow storage independently of compute.
- ClickHouse integrates PostgreSQL with a separate ClickHouse analytical service. Compare the full architecture, including standbys, backups, replicas, and analytical capacity.
ClickHouse Managed Postgres vs Crunchy Bridge at a glance
ClickHouse Managed Postgres runs production PostgreSQL workloads on local NVMe within ClickHouse Cloud. Its managed replication path connects Postgres to a separately provisioned ClickHouse analytical service. ClickHouse’s acquisition of Xata aims to add scale-to-zero and copy-on-write branching to the service.
Crunchy Bridge is Crunchy Data's managed PostgreSQL service across AWS, Google Cloud, and Azure. It runs transactional applications and agent backends, with independent storage sizing and broad PostgreSQL tooling.
| Dimension | ClickHouse Managed Postgres | Crunchy Bridge |
|---|---|---|
| Best-fit workloads | AI agent and application backends with performance-critical workloads, integrated operational tooling, or growing analytical demand | AI agent and application backends needing flexible storage sizing, broad PostgreSQL tooling, or multi-cloud deployment |
| Storage | Local NVMe bundled with the VM configuration | AWS gp3 sized independently of compute |
| Storage growth | Storage grows through VM configuration changes | Storage grows independently of compute |
| HA | No standby, one asynchronous standby, or two synchronous-quorum standbys | No standby, or one hidden hot standby on eligible non-Hobby plans |
| Pooling | PgBouncer transaction pooling | PgBouncer transaction and session modes. Unavailable on Hobby |
| Retrieval | pgvector, full-text and BM25 options. pg_clickhouse pushes vector and search queries to ClickHouse for retrieval beyond PostgreSQL scale | pgvector, full-text and BM25 options |
| Isolated development copies | Restore-based branches. Copy-on-write branching planned through the Xata acquisition | Restore-based forks |
| Diagnostics and agent tools | Remote MCP, ClickHouse Agents, clickhousectl CLI, query Insights, metrics and logs | Database Insights, cb scope, metrics and log export |
| Standard backup retention | One day on Basic, seven days on Scale | Ten days |
| Pricing | Complete NVMe VM configurations plus selected standbys | Separate instance and storage rates. HA doubles the cluster price |
| Analytics | Read replicas and integrated replication to a separate ClickHouse service | Read replicas and external analytical replication or query access |
Bridge's PostgreSQL version policy lists versions 15 through 18. New version 15 provisioning has been limited since May 11, 2026, with availability ending May 10, 2027. ClickHouse's OpenAPI guide identifies 17 as the default and demonstrates provisioning 18. Select the required version and extensions for the target cloud and region.
PostgreSQL storage and scaling: local NVMe vs network storage
ClickHouse Managed Postgres stores data on server-local NVMe drives attached to the database server. Crunchy Bridge on AWS uses gp3 block storage, with disk capacity sized independently of compute.
Local NVMe removes the network-storage hop from disk reads and writes. Disk-bound transactions benefit from that shorter path. Queries served from memory depend more on CPU, indexes, and concurrency. For agent applications, storage behavior affects checkpoints and context queries that hit disk.
ClickHouse packages storage with the selected VM. To resize an instance, ClickHouse restores a new instance, lets it catch up, and does a controlled failover. Storage autoscaling also moves the database to a configuration with more capacity, so growth follows the available VM sizes. The Xata acquisition aims to bring scale-to-zero to ClickHouse Managed Postgres.
Crunchy Bridge attempts online storage growth before falling back to a replacement machine when cloud-provider restrictions prevent it. Storage increases also apply to the HA standby. Changing instance size or tier uses a new machine and briefly interrupts connections. The connection string stays the same, but your application has to reconnect.
ClickHouse Managed Postgres vs Crunchy Bridge: performance benchmarks
ClickHouse's PostgresBench measures transactional throughput using pgbench's TPC-B-like workload. Its source code and methodology make the tests reproducible. The published results compare complete service configurations, including their storage and HA settings. They don't measure end-to-end agent latency or vector retrieval.
HA-disabled throughput at two instance sizes
The HA-disabled tests use 256 clients, 16 threads, prepared queries, and three 600-second runs per service in AWS us-east-2. The listed configurations run PostgreSQL 18.3 with provider-default settings. The values below are three-run means.
| HA-disabled configuration | ClickHouse Managed Postgres (TPS) | Crunchy Bridge (TPS) |
|---|---|---|
| 16 vCPUs, 64 GB RAM, about 500 GB data | 26,105 | 10,954 |
| 4 vCPUs, 16 GB RAM, about 100 GB data | 6,013 | 6,320 |
TPS means transactions per second.
At 16 vCPUs and 64 GB RAM, ClickHouse Managed Postgres delivered substantially higher throughput in the HA-disabled benchmark. At 4 vCPUs and 16 GB RAM, the services deliver comparable throughput, with Crunchy Bridge about 5% higher in this test. Equal CPU and memory counts don't imply identical processors, storage, or prices. The relevant result depends on the instance size and transaction mix your application will use.
Throughput and latency with HA enabled
ClickHouse's PostgresBench HA comparison tests 16 vCPUs, 64 GB RAM, and about 500 GB of data. Its table publishes the following results, including single-node baselines drawn from the HA-disabled test set.
| Service and configuration | Published throughput (TPS) | Average latency (ms) | p99 latency (ms) |
|---|---|---|---|
| ClickHouse Managed Postgres, single node | 26,328 | 9.70 | 13.20 |
| ClickHouse Managed Postgres, one asynchronous standby | 24,667 | 10.37 | 24.17 |
| ClickHouse Managed Postgres, two synchronous-quorum standbys | 20,720 | 12.34 | 33.49 |
| Crunchy Bridge, single node | 11,113 | 23.00 | 41.68 |
| Crunchy Bridge, HA with one standby, labeled asynchronous by ClickHouse | 11,135 | 23.00 | 41.89 |
The 26,328 TPS ClickHouse baseline comes from an individual run, while 26,105 TPS above is the three-run mean. The two tables draw on overlapping benchmark data. The latency column reports averages.
ClickHouse's synchronous-quorum configuration waits for standby acknowledgement before completing a commit. In this test, it delivered lower throughput and higher p99 latency than the single-node configuration. Compare performance using the durability mode your application requires. Bridge's similar single-node and HA results describe its tested configuration. They don't prove its contractual durability guarantee. The publication measures HA's performance cost. It doesn't supply a failure-injection or recovery assessment.
Agent and developer workflows: retrieval, pooling, branching, and MCP
Example: a support agent's database workload
Take a support agent that reads account and conversation history, retrieves relevant context, saves checkpoints, and updates a support ticket. Both services can keep the account, ticket, and current agent state in Postgres, with pgvector or keyword queries supplying context.
Teams analyze recorded runs and tool outcomes to improve the application. The agent may also query historical business data while composing a response. If those scans interfere with live transactions, route suitable reads to a replica or replicate history to a separate analytical service. Operators use database diagnostics to investigate slow queries and resource pressure.
LangGraph checkpointing and PostgreSQL state persistence
LangGraph checkpoints at super-step boundaries and records task-level pending writes for fault tolerance. Its persistence modes include synchronous, asynchronous, and exit-only. The PostgreSQL saver uses Psycopg 3, and manually supplied connections require autocommit=True and dict_row.
Other agent frameworks and custom tool loops differ in how they execute work, but frequent state reads, writes, and context lookups create similar database demands. Checkpoint frequency, state size, concurrency, and transaction behavior determine how much database capacity each application needs.
PgBouncer connection pooling and session compatibility
Both services provide PgBouncer transaction pooling. Crunchy Bridge also supports session pooling. PgBouncer isn't available on Hobby plans. Bridge's pooler setup requires the crunchy_pooler extension in each database using the pooled endpoint.
Transaction pooling reuses PostgreSQL backends across client transactions, letting many short-lived application or function connections share a smaller backend pool. Session advisory locks and LISTEN need a session-preserving connection. Sending NOTIFY works in transaction mode. Protocol-level prepared statements require compatible PgBouncer settings and driver behavior. SQL-level PREPARE carries a separate limitation.
ClickHouse's connection limits example illustrates 2,500 pooler clients sharing 500 PostgreSQL backends. Pooling accommodates connection bursts, while concurrent database work still depends on backend capacity. Confirm both limits for the selected plan, then test the saver, prepared statements, retries, and reconnects through your application's endpoint.
Vector and hybrid search: pgvector, HNSW, and BM25
Both services support pgvector and PostgreSQL full-text search. ClickHouse Managed Postgres includes pgvector 0.8.6 with IVFFlat and HNSW. Crunchy Bridge provides pgvector on all clusters, including HNSW support. Check the installed extension version on the target cluster for either service.
Vector similarity retrieves semantically related context. Keyword and fuzzy matching help with exact terms, identifiers, and misspellings. ClickHouse Managed Postgres also supports VectorChord and BM25 retrieval. Bridge offers BM25 through pg_textsearch on PostgreSQL 17 and 18, requiring a current cluster image and preload configuration. Applications combine and rank vector and keyword results in SQL or application code. When retrieval workloads outgrow PostgreSQL capacity, teams using ClickHouse Managed Postgres can store vectors and search indexes in ClickHouse and query them through PostgreSQL via pg_clickhouse. ClickHouse handles vector and text search at scales beyond what PostgreSQL extensions support, while the application retains its PostgreSQL interface.
Upstream pgvector stores 4 × dimensions + 8 bytes per vector. One million 1,536-dimensional vectors take about 6.15 GB of raw vector values before row, index, and WAL overhead. Size the database for this retrieval data alongside checkpoints and application records. Then test recall, latency, and tenant-filtered retrieval while representative state writes run.
| Extension | ClickHouse Managed Postgres | Crunchy Bridge |
|---|---|---|
pg_trgm |
Available | Available |
| PostGIS | Available | Available, including PostGIS Raster |
pg_cron |
Available | Available in preload configuration |
pg_stat_statements |
Available | Available in preload configuration |
| ClickHouse query access | Available: pg_clickhouse preinstalled
|
Available: clickhouse_fdw
|
Database branching, forks, and provisioning tools
| Workflow | ClickHouse Managed Postgres | Crunchy Bridge |
|---|---|---|
| API automation | OpenAPI management API | Bridge management API |
| Command-line automation | clickhousectl CLI |
cb CLI |
| Infrastructure as code | Postgres Terraform resource in alpha | Bridge Terraform provider |
| Isolated database copy | ClickHouse database branches | Crunchy Bridge PITR forks |
| Dedicated read scaling | ClickHouse read replicas | Bridge read replicas |
Branches and forks restore a base backup and replay WAL into an independent deployment. They work for migration rehearsals, index experiments, and debugging against realistic data. For short-lived tests, account for provisioning time and the cost of a separate running database. Production-derived copies also need masking and access controls. Copy-on-write branching is planned for ClickHouse Managed Postgres through the Xata acquisition.
Read replicas serve lag-tolerant reads separately from the writer. ClickHouse replicas use archived-WAL shipping by default, and support can configure lower-lag replication options. Bridge replicas have independently chosen compute and the primary's storage size, with cross-region and cross-provider deployments supported. Keep reads on the primary when an agent must see the latest committed checkpoint. HA standbys aren't the same as these application read endpoints.
PostgreSQL monitoring and MCP integration
ClickHouse Managed Postgres brings service metrics, Query Insights, and PostgreSQL logs into ClickHouse Cloud. Its ClickHouse Cloud remote MCP server gives compatible agents read-only PostgreSQL queries, service metrics, and slow-query investigation. Running PostgreSQL queries through MCP requires OAuth. API-key authentication can't run that query tool.
ClickHouse Agents for Managed Postgres provides an interface for exploring data and investigating performance across Postgres and ClickHouse. Teams use it to dig into retrieval queries, state updates, and resource pressure when agent steps or application requests slow down.
Crunchy Bridge provides Database Insights and cb scope, system metrics, and log export. Teams can investigate long-running queries, index use, bloat, vacuum activity, and connections when diagnosing slow agent steps or application requests.
Application agents read and write through PostgreSQL drivers or custom tool integrations on either service, using the permissions assigned to those integrations. ClickHouse's remote MCP adds read-only data exploration and database diagnostics on top.
High availability, backups, and PostgreSQL upgrades
HA keeps a standby available for primary failure. Backups and point-in-time recovery (PITR) restore earlier database state. Agent applications need both a recovery time objective (RTO) for acceptable downtime and a recovery point objective (RPO) for acceptable data loss.
HA modes and commit-path trade-offs
ClickHouse Managed Postgres HA offers no standby, one asynchronous standby, or two synchronous-quorum standbys. With no standby, recovery can take longer. Asynchronous commits don't wait for the standby, so recent committed transactions can be lost if the primary fails before replication catches up. With two synchronous standbys, a commit waits for acknowledgement from at least one.
Crunchy Bridge HA uses a hidden hot standby sized like the primary. On failure, Bridge promotes it and creates a replacement standby. Existing sessions drop even though the connection string stays the same. Standard and Memory-optimized clusters with HA carry a 99.95% uptime SLA.
Bridge's public HA description doesn't specify synchronous acknowledgement or a numeric RPO/RTO. ClickHouse labels its tested Bridge configuration asynchronous. Confirm Bridge's commitment for the selected deployment before treating the two services' HA durability guarantees as equivalent.
Backup retention and point-in-time recovery (PITR)
Both services automate physical backups and archive WAL every 60 seconds or 16 MB, whichever comes first.
| Recovery capability | ClickHouse Managed Postgres | Crunchy Bridge |
|---|---|---|
| Standard backup retention | One day on Basic, seven days on Scale | Ten days |
| PITR destination | Restore into a new instance | Restore into a new fork |
| Extended retention | Longer retention requires support | Daily, weekly, monthly, and yearly backups configurable |
| 30-day continuous PITR | Confirm availability and pricing with support. No standard 30-day PITR price is published | Extended restore points don't provide continuous PITR throughout the 30-day period |
Bridge's extended backups keep enough WAL to recover each selected snapshot, rather than the full intervening history. Specify daily restore points or continuous PITR when requesting a longer retention policy.
Maintenance and upgrades
ClickHouse uses failover-based upgrades with configurable scheduling, typically interrupting service for a few seconds.
Crunchy Bridge provides a three-hour maintenance window, with none configured by default. Its major-version upgrade uses a hidden upgrade standby and a write halt. A successful upgrade can't roll back in place. Post-upgrade analyze and backup add I/O work.
Applications must reconnect and handle interrupted transactions after either service's lifecycle events.
Pricing comparison and total deployment cost
ClickHouse Managed Postgres prices complete VM configurations, while Crunchy Bridge prices compute and storage separately. Region, service tier, capacity, and HA requirements determine the base deployment cost. Replicas, development databases, backups, support, and analytics add to the full bill.
Pricing models and cost drivers
| Price driver | ClickHouse Managed Postgres | Crunchy Bridge |
|---|---|---|
| Primary capacity | A complete VM configuration bundles CPU, memory, and local NVMe storage | A compute plan and separately sized storage determine the primary's cost |
| Storage growth | More storage requires selecting another NVMe VM configuration | Storage can grow independently of compute |
| High availability | Selected standby VMs add to the primary configuration's cost | HA doubles the cluster price, including compute and storage |
| Backup storage | An allowance covers backup storage up to provisioned disk capacity. Excess bytes bill separately | Standard backups are included. Extended backups add charges based on storage size |
| Replicas and development copies | Additional deployments consume their own provisioned resources | Additional deployments consume their own provisioned resources |
| Support | Included support and response commitments depend on the organization tier | Standard support is included. Paid support tiers add response and escalation commitments |
| Analytics | Replication from Managed Postgres to ClickHouse is free. Analytical compute and storage bill separately | Include the selected connector and analytical destination's costs |
How to compare total PostgreSQL deployment costs
Compare deployments that meet the same throughput, latency, usable-storage, and recovery requirements. ClickHouse's bundled NVMe configurations and Bridge's independent storage sizing affect how each deployment grows as agent state, retrieval indexes, and application records accumulate.
Include applicable network transfer, support, and additional databases or analytical services. ClickHouse bills data transfer at ClickHouse Cloud rates. For longer backup retention, specify whether your application needs periodic restore points or continuous point-in-time recovery.
PostgreSQL read replicas and ClickHouse analytics integration
Agent traces, tool-call audits, and token-cost records can start in Postgres. A separate analytical service lets teams scale analytical queries and historical retention separately from the database serving transactions and current agent state.
AI agent analytics: execution traces and business history
Teams analyze recorded runs, tool outcomes, evaluations, latency, token usage, and costs to improve an agent application. Application instrumentation supplies the traces and relationships among model and tool calls. The database stores and queries those records.
Application agents also query historical events and business aggregates while answering questions or completing tasks.
ClickPipes replication and PostgreSQL analytics alternatives
The ClickPipes setup for Managed Postgres connects Postgres to an existing or new ClickHouse service. Use an initial load to copy existing rows, change data capture (CDC) to capture ongoing changes, or both. A primary key or supported replica identity is required.
| Analytical path | Query execution | Setup and consistency |
|---|---|---|
| ClickHouse Managed Postgres → ClickHouse | ClickHouse engine on separate compute and storage within the same platform | Integrated ClickPipes setup with asynchronous replication and eventual consistency |
| Crunchy Bridge → external analytics | Selected destination's query engine, including ClickHouse | Logical replication and an external connector. Consistency depends on the path |
| Dedicated PostgreSQL read replica on either service | PostgreSQL engine on separate replica compute | Application routes reads. Replication lag affects freshness |
| Foreign-table query access | Remote ClickHouse for supported operations | ClickHouse's pg_clickhouse or Bridge's clickhouse_fdw. Query access differs from replication |
PostgreSQL read replicas move lag-tolerant reads off the writer while keeping PostgreSQL's query engine. A separate ClickHouse service runs analytical queries on a columnar engine with its own compute, storage, and replicated copy. ClickHouse integrates the replication setup and management within its platform. Bridge can also feed or query an external analytical system.
Replication lag, PostgreSQL source overhead, and query pushdown
ClickPipes uses a 60-second default sync interval for its Managed Postgres-to-ClickHouse integration. Measure end-to-end lag separately: scheduling, source activity, transfer, and apply work all affect freshness. Replication runs asynchronously, so the analytical copy stays eventually consistent.
Updates and deletes use versioned rows and deletion markers, with asynchronous deduplication. Replication slots retain WAL on the source. Decoding, snapshots, and network transfer also consume source resources. Moving analytical queries to ClickHouse separates query execution but leaves that replication work in Postgres. If the application uses TRUNCATE to clear tables, plan how to clear the analytical copy too: ClickPipes doesn't replicate that operation.
pg_clickhouse provides remote query execution and a foreign data wrapper. It doesn't replicate data. Pushdown depends on the supported pg_clickhouse operations. Use EXPLAIN to confirm which operations run in ClickHouse before relying on remote execution to relieve the PostgreSQL workload. Use Postgres for reads that need current transactional state.
Analytics integration costs: replication, compute, and storage
| Cost component | ClickHouse Managed Postgres → ClickHouse | Crunchy Bridge → external analytics |
|---|---|---|
| Source database | Primary, HA, backups, and any read replicas | Primary, HA, backups, and any read replicas |
| Replication | Free replication from Managed Postgres to ClickHouse, through ClickPipes or WalShadow | Connector-specific charges. When using ClickPipes, general CDC billing includes data and connector compute |
| Source network | Applicable transfer charges for the selected route | Applicable transfer charges for the selected route |
| Analytical service | Separately provisioned ClickHouse compute and storage on the Cloud bill, including required retention and support | Selected destination's compute and storage, including required retention and support |
General ClickPipes connector rates don't apply to the free replication path from Managed Postgres to ClickHouse. Budget analytical capacity separately from the transactional service on either architecture.
Migrating between Crunchy Bridge and ClickHouse Managed Postgres
Moving from Crunchy Bridge to ClickHouse Managed Postgres
The ClickPipes migration wizard migrates data from Crunchy Bridge into the transactional ClickHouse Managed Postgres service, using an initial load and optional CDC. Replication into the ClickHouse analytical service is a separate workflow.
Before starting, check PostgreSQL versions, extensions, roles, schema objects, replica identity, and network access.
For the CDC migration path, complete the initial load, stop source writes, let replication catch up, validate the target, pause replication, reset sequences, and switch application connections. Verify application reads and writes before removing source replication slots and retiring the old deployment.
Moving from ClickHouse Managed Postgres to Crunchy Bridge
Crunchy Bridge supports dump/restore and PostgreSQL replication migration paths. Dump/restore suits a planned write outage. Replication reduces the data-transfer work left for cutover when the source configuration supports it.
Check roles, extensions, schema objects, and sequence state in this direction too. With replication, stop source writes before final catch-up and validation, then switch connections. Update any ClickHouse-specific provisioning scripts and diagnostic integrations to use Bridge's APIs, CLI, and monitoring tools before retiring the ClickHouse deployment.
Which PostgreSQL service fits an AI agent application?
ClickHouse Managed Postgres is the stronger fit for agent and application backends where transactional throughput, integrated diagnostics, or ClickHouse analytics matter most. The Xata acquisition aims to add scale-to-zero and copy-on-write branching. Local NVMe handles the transactional work, selectable HA controls the standby topology, and the ClickHouse integration provides a path to analytical queries on separate resources.
Crunchy Bridge is the stronger fit when you need storage that grows independently of compute, broad PostgreSQL extension and configuration support, or deployment across AWS, Google Cloud, and Azure. Its API, CLI, forks, and monitoring support application development and operations.
Match the standby configuration to acceptable data loss and downtime, then compare the complete deployment.
Evaluation checklist:
- Reproduce representative transactions with the required durability settings, schema, connection count, and region.
- Exercise the agent framework through its pooled or direct endpoint.
- Check required extensions and index operations on the selected cluster.
- Include HA, backups, egress, support, and any analytical service in the cost model.
- Rehearse restores, failover, and application reconnection.
Frequently asked questions about ClickHouse Managed Postgres and Crunchy Bridge
Which service fits an AI agent application better?
ClickHouse Managed Postgres suits agent backends where throughput and integrated tooling are priorities. Crunchy Bridge suits workloads that need flexible storage sizing, broad PostgreSQL tooling, or multi-cloud deployment. Both support state persistence and retrieval. Their storage, workflow, and recovery choices determine fit.
Does PgBouncer transaction pooling work with LangGraph's PostgreSQL saver?
Compatibility depends on the deployed saver, driver, pooler settings, and session requirements. Manually supplied saver connections require autocommit=True and dict_row. Test checkpoint writes, resume, and retries through the intended endpoint. Session advisory locks and LISTEN need a session-preserving connection. Sending NOTIFY works in transaction pooling. Bridge also offers session pooling. The connection-compatibility section explains the endpoint choice.
Do both services support pgvector and HNSW indexes?
Yes. ClickHouse Managed Postgres lists pgvector 0.8.6 with IVFFlat and HNSW. Bridge offers pgvector on all clusters and supports HNSW. Confirm the installed extension version, then test tenant filters, recall, and behavior under concurrent writes on the target cluster. Both also provide keyword and BM25 retrieval options.
Does ClickHouse Managed Postgres support MCP?
Yes. The ClickHouse Cloud remote MCP server provides read-only PostgreSQL queries, service metrics, and slow-query tools. Running PostgreSQL queries through MCP requires OAuth. Cloud API-key authentication doesn't work for those queries. These MCP tools let compatible agents explore data and investigate PostgreSQL performance. Application writes need a separate database integration.
How do database branching and forks compare?
ClickHouse branches and Bridge forks create independent deployments by restoring backups and replaying WAL. Copy-on-write branching is planned for ClickHouse Managed Postgres through the Xata acquisition. Both work for staging, migration rehearsals, and debugging against realistic data. Account for creation time, running-database cost, masking, and cleanup in development-copy workflows.
Which runs faster: ClickHouse Managed Postgres or Crunchy Bridge?
In the published HA-disabled PostgresBench tests, ClickHouse delivers substantially higher throughput at the larger configuration. The services deliver comparable results at the smaller configuration, with Crunchy Bridge about 5% higher in that test. These results measure pgbench-style transactions. Measure completed checkpoints or tasks, transaction latency, and pool queue time with your application's queries and required HA configuration. Keep three-run means and published HA figures distinct.
Does ClickHouse Managed Postgres cost less than Crunchy Bridge?
The lower-cost option depends on the resources needed to meet your application's performance and recovery requirements. ClickHouse bundles CPU, memory, and NVMe storage in each VM configuration. Bridge prices compute and storage separately. Compare the pricing models and deployment requirements, including HA, replicas, backup policy, network transfer, support, and analytical capacity.
Can Crunchy Bridge replicate data to ClickHouse for analytics?
Yes. Bridge supports logical replication into external systems, including a connector path to ClickHouse. ClickHouse Managed Postgres integrates that setup within ClickHouse Cloud and provides free replication from its own Postgres service. Analytical compute and storage bill separately. Both paths require attention to freshness and source load.
How does migration from Crunchy Bridge to ClickHouse Managed Postgres work?
The ClickPipes migration wizard supports Crunchy Bridge sources. For the CDC migration path, complete the initial load, stop source writes, let replication catch up, validate the target, pause replication, reset sequences, and switch application connections. Verify the application before removing source replication slots. The migration section also covers the reverse direction.
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