Introduction
Data replication underlies a lot of modern systems: ensuring uptime (high availability), preparing for disasters (disaster recovery), feeding analytics or BI pipelines, doing migrations, or supporting global apps / multi-region data requirements. But not all replication tools or strategies are the same. Key trade-offs include:
- How you capture changes (log-based / trigger-based / polling / bulk loads)
- How “real time” the sync must be (is minutes okay, or do you need near-instantaneous?)
- Whether source and destination use the same DB engine or different ones (“homogeneous vs heterogeneous”)
- How you deal with schema differences, evolving schemas, identity / sequences, computed fields, etc.
- What conflicts might arise if you have more than one writer, how those are resolved
- Operational complexity, monitoring, cost, licensing, etc.
Each major relational database (Oracle, SQL Server, MySQL, PostgreSQL…) has its own internal mechanisms (redo logs, transaction logs, binlogs, WALs, etc.), data type nuances, and limitations. Cross-engine replication often magnifies mismatches (for example, SQL Server NVARCHAR(MAX) vs PostgreSQL TEXT; Oracle NUMBER vs SQL Server DECIMAL; MySQL JSON vs SQL Server JSON stored as NVARCHAR).
Below is a comparison of leading tools (including a few people often miss), where they fit, what to avoid, and how to mitigate the common pain points. Because this is a SQL Server blog, you’ll see SQL Server compatibility called out for each tool.
Native SQL Server options (know these first)
If you can solve the problem natively, start here.
- Transactional Replication: log-based, near-real-time, typically server-to-server. Good for reporting offload and scale-out reads. Supports peer-to-peer for multi-node scale-out, but conflict handling is limited and design matters. Microsoft Learn+2Microsoft Learn+2
- Merge Replication: designed for occasionally connected scenarios and multi-site writes, with built-in conflict detection/resolution. More overhead than transactional for many OLTP cases. Microsoft Learn
- Always On Availability Groups: HA/DR, not a cross-engine replication tool. Great for failover and readable secondaries; use distributed AGs for cross-region. Not a schema-mapping solution. Microsoft Learn+1
- Change Data Capture (CDC): records row-level changes into change tables. Often used to feed downstream pipelines or third-party CDC tools. Requires enabling at the DB and table level. Microsoft Learn+1
- Change Tracking (CT): lighter than CDC, tells you “what changed” without full before/after values. Handy for app-level sync and low-overhead pipelines. Microsoft Learn
When native fits best: same-engine topologies, HA/DR, classic reporting replicas, or when you can use CDC/CT to push changes into a warehouse or stream without introducing new infrastructure. When it’s not enough: cross-engine migrations, active-active with custom conflict logic, or broad connector ecosystems.
The 8 decisions that shape your replication
- Latency target (sub-second vs seconds/minutes/batch)
- Directionality (one-way vs bidirectional vs multi-master)
- Homogeneous vs heterogeneous (same engine vs cross-engine)
- Schema evolution plan (how DDL flows)
- Conflict handling (rules, detection, prevention)
- Filtering (whole DB vs selected tables/rows/columns)
- Ops overhead (install, monitor, recover)
- Cost / lock-in (licenses, infra, people time)
Tool-by-tool, with SQL Server compatibility
Oracle GoldenGate
How it works: enterprise log-based CDC, heterogeneous, supports bidirectional.
SQL Server: source ✅ / target ✅ (transaction log capture). Watch type mappings (XML, spatial) and collation differences.
Best when: mission-critical, low-latency, active-active, complex topologies.
Limits to plan for: licensing and operational complexity; schema drift across engines still needs discipline.
Mitigations: supplemental logging, tight DDL governance, rehearsal cutovers.
(Vendor docs are behind portals; details here draw on Microsoft replication and AG docs for native contrasts.)
AWS Database Migration Service (DMS) + Schema Conversion Tool (SCT)
How it works: managed full load plus CDC; SCT helps cross-engine schema mapping.
SQL Server: source ✅ / target ✅. Common use: on-prem SQL Server into AWS RDS/Aurora or EC2. Amazon Web Services, Inc.+1
Best when: one-way migrations or hybrid sync with lower ops burden.
Limits to plan for: not meant for active-active; watch quotas and serverless limitations; computed columns, triggers, constraints often need manual handling; identity/sequence semantics differ across engines. AWS Documentation+1
Mitigations: precreate target tables for exact types, run SCT ahead of time, right-size replication instances, monitor task lag and cached changes. AWS Documentation
Debezium + Kafka (or Debezium Server to Kinesis/Pulsar)
How it works: open-source, log-based CDC connectors publish change events; consumers fan out to many targets.
SQL Server: source ✅ via the official connector that relies on SQL Server CDC. Good for OLTP-to-streams and analytics. Debezium
Best when: real-time streaming into multiple targets, event-driven architectures, replayability.
Limits to plan for: more moving parts, at-least-once delivery (handle duplicates), DDL coordination required. Debezium
Mitigations: schema registry, idempotent sinks, thoughtful partitioning. Confluent Documentation
Quest SharePlex
How it works: low-impact streaming replication with strong support for Oracle and PostgreSQL, including active-active and conflict detection/resolution, plus compare and repair tools. Quest+2The Quest Blog+2
SQL Server: source ❌ / target ✅ (in some topologies). Primary focus is Oracle↔Postgres and Postgres↔Postgres. Check current release notes if you need SQL Server targets. Quest+1
Best when: minimal-downtime migrations Oracle↔Postgres, cross-region Postgres active-active, reporting offload with integrity checks. The Quest Blog
Limits to plan for: focused source coverage, licensing, exotic types/DDL require planning.
Mitigations: define conflict rules up front, use compare/repair to maintain consistency, validate throughput with real data. Quest Support
DBConvert Streams
How it works: CDC replication and migrations, container-friendly, API-driven. Good for heterogeneous sync without building Kafka yourself. DBConvert Streams+1
SQL Server: source ✅ / target ✅ (see product pages and SQL Server guides). dbconvert.com+1
Best when: you want straightforward cross-engine sync or analytics feeds with simpler ops than a DIY CDC stack.
Limits to plan for: not as battle-tested at extreme scale as the big enterprise tools; still do a POC for high-volume CDC and conflict needs.
Mitigations: pre-map LOBs and computed columns, monitor lag and backpressure, validate with your data. DBConvert Streams
Qlik Replicate
How it works: enterprise replication and ingestion with real-time CDC, wide connector set, and Kafka integrations. Qlik+1
SQL Server: source ✅ / target ✅, including AG considerations and supported types. Qlik Help+2Qlik Help+2
Best when: polished UI and monitoring matter, and you want a supported path from SQL Server into warehouses or Kafka with minimal custom code.
Limits to plan for: licensing; still need DDL discipline and endpoint tuning.
Mitigations: enable CDC correctly on source, test data type mappings, size endpoints. Qlik Community
SymmetricDS (open source)
How it works: multi-master, filtered synchronization, works over low-bandwidth or intermittent links; trigger- or log-based depending on DB. SymmetricDS+1
SQL Server: source ✅ / target ✅. Often used when many sites write and links are unreliable. Wikipedia
Best when: budget is tight, topology is hybrid or edge, or you need multi-master beyond a single DC.
Limits to plan for: more ops to tune and monitor; performance overhead under heavy OLTP.
Mitigations: limit overlapping write domains, simulate conflicts, monitor batches and throughput. SymmetricDS
Striim
How it works: CDC platform with readers for SQL Server, targets include Snowflake and others; managed and self-hosted options. Striim+1
SQL Server: source ✅ / target ✅ with MS SQL Reader or MSJet for CDC. Striim
Best when: you want a managed-feel CDC stack to feed warehouses or streams with sub-second targets.
Limits to plan for: licensing; still need topology/backpressure design.
Mitigations: pick the right reader (throughput vs compatibility), test end-to-end latency to your warehouse/stream. Striim+1
Real-world scenarios (with SQL Server)
- SQL Server on-prem to AWS RDS/Aurora SQL Server
Use DMS + SCT for one-way migration with minimal ops. Precreate tables for exact types, then run CDC until cutover. Amazon Web Services, Inc. - SQL Server OLTP to Snowflake or other warehouses
Use Qlik Replicate or Striim for managed pipelines; or Debezium if you want open-source and Kafka fan-out. Qlik Help+2Striim+2 - SQL Server multi-site writes
Prefer native peer-to-peer transactional replication or SymmetricDS if you need multi-DB and offline tolerance. Plan conflict rules carefully. GitHub+1 - SQL Server to PostgreSQL migration
Start with DMS + SCT or DBConvert Streams. Validate identity/sequence handling and LOB types. AWS Documentation+1
Common failure modes and how to avoid them
- Data type mismatches
Identity vs sequences, GUID vs UUID, JSON handling. Precreate targets or run schema conversion to lock types. AWS Documentation - Silent schema drift
DDL in production without coordination can stall or break CDC. Gate DDL, version schemas, and test tool behavior on DDL. - Bidirectional conflicts
Define precedence (timestamp or source priority). Prevent write overlaps. SharePlex and SQL Server peer-to-peer have conflict features, but your policy matters most. The Quest Blog+1 - Lag and backpressure
Right-size replication compute, isolate I/O, and filter noisy tables. For DMS, monitor task lag and quotas; for Kafka pipelines, use idempotent consumers. AWS Documentation - Ops blind spots
Add heartbeats, lag dashboards, exception queues. Tools like SharePlex have compare/repair to heal drift. Quest Support
Quick decision guide
- Same-engine SQL Server HA/DR or read replicas: use Always On AG or Transactional Replication first. Microsoft Learn+1
- One-way SQL Server to AWS: DMS + SCT. AWS Documentation
- SQL Server to many downstreams / event-driven: Debezium + Kafka. Debezium
- Enterprise pipelines with UI and support: Qlik Replicate or Striim. Qlik Help+1
- Heterogeneous sync without heavy ops: DBConvert Streams. DBConvert Streams
- Multi-master across sites with mixed engines: SymmetricDS. SymmetricDS
Ranked recommendations (SQL Server context)
| Rank | Tool | SQL Server support | Best for |
|---|---|---|---|
| 1 | Native: AG + Transactional Replication | native | HA/DR and read-scale with minimal moving parts. Microsoft Learn+1 |
| 2 | Oracle GoldenGate | source ✅ / target ✅ | Enterprise heterogeneous and active-active where budget allows. |
| 3 | Debezium + Kafka | source ✅ | Streaming pipelines and multi-target fan-out. Debezium |
| 4 | AWS DMS + SCT | source ✅ / target ✅ | One-way migrations into AWS. AWS Documentation |
| 5 | Qlik Replicate | source ✅ / target ✅ | Real-time SQL Server to warehouse or Kafka with strong tooling. Qlik Help |
| 6 | Striim | source ✅ / target ✅ | Managed-feel CDC with sub-second targets. Striim |
| 7 | DBConvert Streams | source ✅ / target ✅ | Mid-scale heterogeneous sync and migrations. DBConvert Streams |
| 8 | SymmetricDS | source ✅ / target ✅ | Open-source multi-master across sites. SymmetricDS |
| 9 | SharePlex | source ❌ / target ✅ (limited) | Strong for Oracle↔Postgres; consider only if SQL Server is downstream. Quest |
References
SQL Server native features
- SQL Server Replication overview and Transactional Replication docs, Microsoft Learn. Microsoft Learn+1
- Peer-to-peer transactional replication, Microsoft docs. GitHub
- Always On availability groups overview and getting started, Microsoft Learn. Microsoft Learn+1
- Change Data Capture (CDC) and Change Tracking (CT), Microsoft Learn. Microsoft Learn+2Microsoft Learn+2
AWS DMS
- AWS DMS service overview and user guide. Amazon Web Services, Inc.+1
- Quotas and serverless limitations. AWS Documentation+1
Debezium
- Debezium SQL Server connector and source connector docs. Debezium+1
- List of Debezium source connectors. Debezium
Quest SharePlex
- Product page and Azure marketplace overview. Quest+1
- PostgreSQL active-active and conflict handling notes. The Quest Blog
- Compare and repair utilities. Quest Support
DBConvert Streams
- Docs and CDC overview. DBConvert Streams+1
- SQL Server migration/sync pages. dbconvert.com
Qlik Replicate
- SQL Server as source and target; Kafka integrations. Qlik Help+2Qlik Help+2
SymmetricDS
- Docs, FAQ, and overview of multi-master, filtered sync. SymmetricDS+2SymmetricDS+2
Striim
- SQL Server CDC readers and SQL Server connector docs; Snowflake writer. Striim+2Striim+2
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