How to choose a change data capture tool

Change data capture reads a database's own transaction log — the write-ahead log in PostgreSQL, the binlog in MySQL, the redo log in Oracle — and turns every committed insert, update and delete into an event. Because it reads the log rather than repeatedly querying tables, it adds little to no load on the source database and can deliver changes downstream in seconds rather than the hours a nightly batch extract takes. Analytics teams use it to keep a warehouse current without hammering production; engineering teams use it to feed caches, search indexes and other services with a live copy of the data.

You don't need it if a batch sync once or a few times a day is genuinely fine — most ELT connectors already handle that more simply, and running a CDC pipeline is more operational surface than a scheduled extract. CDC earns its cost when staleness of hours actually breaks something: a support agent looking at an order that isn't there yet, a fraud model scoring on data that's already out of date, or a downstream system that needs every state a row passed through, not just its final value.

Log-based vs query-based, and how many databases it speaks

Every tool here is log-based, which is the right default — query-based ("poll and diff") CDC re-reads tables on a schedule and misses intermediate states, plus it costs the source database real query load. Where they differ is breadth. Debezium, Striim, Oracle GoldenGate and Qlik Replicate cover a wide span of databases and, for the latter two, mainframes. Maxwell's Daemon deliberately does one thing: it tails MySQL binlogs and nothing else. The newer managed entrants — Artie, Decodable, Streamkap — concentrate on the common sources (PostgreSQL, MySQL, MongoDB) feeding into a warehouse or lake, rather than trying to match the enterprise tools' database count.

Who has to run it

This is the decision that determines your headcount, not just your invoice. Debezium and Maxwell's Daemon are free, open-source software, but "free" means you operate them: Debezium needs a Kafka cluster and Kafka Connect running somewhere, Maxwell needs a host and an output target. Artie, Streamkap and Decodable are fully managed — you point them at a source and a destination and there's no cluster to patch. Oracle GoldenGate, Qlik Replicate and Striim sit in between: all three offer both a self-hosted product and a managed cloud edition, aimed at enterprises with mainframes or legacy databases that need a vendor to call when replication breaks at 2 a.m.

Latency you'll pay for, and what happens in flight

Vendors quote specific numbers because CDC buyers shop on latency: Streamkap cites P99 latency under 250 milliseconds, Artie cites 10–20 seconds typical and under a minute worst case, Oracle GoldenGate cites sub-second replication for active-active database synchronization. Decide what your use case actually needs before you shop on this number — a warehouse refresh that people check once an hour doesn't benefit from sub-second delivery, and the tools built for it price accordingly. Separately, ask whether anything happens to the data in flight. Decodable is built on Apache Flink specifically so you can write SQL, Java or Python transformations as events move; Striim has its own in-memory SQL language (TQL) for filtering and enriching in flight plus built-in data validation. The rest move changes essentially as-is and leave transformation to whatever reads the destination table.

Deployment and compliance

If data cannot leave your environment, that narrows the field to tools with a genuine self-hosted mode: Debezium, Maxwell's Daemon, Oracle GoldenGate, Qlik Replicate and Striim all run on infrastructure you control; Artie, Decodable and Streamkap are cloud services, though Artie and Streamkap both offer bring-your-own-cloud on their higher tiers for teams that need data to stay inside their own account. If you're replicating regulated data, check compliance explicitly rather than assuming it: Streamkap's Enterprise tier adds HIPAA and PCI DSS compliance, Decodable's Enterprise tier adds HIPAA — neither is included on the entry plans.

Open source vs commercial, and how pricing scales

Debezium and Maxwell's Daemon carry no license cost at all; your spend is entirely the Kafka and compute infrastructure you run them on, which for Debezium in particular is not small. The managed usage-based tools — Artie, Decodable, Streamkap — bill by rows, credits or gigabytes moved per month, each with a free tier sized for evaluation or small pilots. Striim is freemium: a Developer edition free up to 25 million events a month, then quote-based Cloud or Platform pricing beyond that. Oracle GoldenGate and Qlik Replicate are both quote-only, priced through license or consumption negotiated with the vendor — expect a sales cycle, not a self-serve signup, for either.

A shortlist by situation

• Already running Kafka and want the open standard: Debezium is what most other CDC and streaming products build on or compare themselves against.
• MySQL only, and want the smallest possible footprint: Maxwell's Daemon does one job with no coordination service to run.
• Want CDC into a warehouse with nothing to operate: Artie or Streamkap set up connectors in minutes and bill by volume.
• Need CDC plus real in-flight transformation, managed: Decodable gives you Flink-grade processing without running Flink yourself.
• Already on AWS and want migration and ongoing CDC from one service: AWS Database Migration Service is native to Redshift, S3 and IAM.
• Replicating from Oracle, mainframes, or other legacy enterprise systems: Oracle GoldenGate and Qlik Replicate are built for exactly this, with GoldenGate strongest on Oracle-to-Oracle active-active and Replicate strongest on agentless, low-impact mainframe extraction.
• Want CDC combined with real-time stream processing and monitoring dashboards: Striim covers both in one product.

Questions to ask a vendor or in a trial

1. What exactly happens to the source database during the initial snapshot — is there a documented load spike, and can it be throttled?
2. How are schema changes on the source handled — automatically propagated, or does the pipeline stop and wait for you?
3. What is the actual, measured end-to-end latency under your data volume, not the marketing number under ideal conditions?
4. What happens to in-flight events if the pipeline needs to restart — do you get exactly-once delivery, at-least-once, or is deduplication your problem downstream?
5. Are backfills and re-syncs billed the same as ongoing replication, or separately?

Common mistakes

Treating CDC output as already clean, conformed data — it is a faithful stream of raw row changes, and someone still has to model it into usable tables. Underestimating the load and duration of the first full snapshot on a large table, which can be the riskiest moment in the whole rollout. Choosing a latency tier you don't need because it was the featured plan in the demo. And not testing what happens on failover or a source database restart before going live — that failure mode is rare enough to skip in a proof of concept and common enough to matter in production.

For two head-to-head looks at specific pairs, see Debezium vs Striim and Oracle GoldenGate vs Qlik Replicate. Every tool in this category is listed at /tools/category/change-data-capture/.