DBSync vs Gluesync

DBSync automates data replication, consolidation, and capture of changes between systems. It supports real-time, two-way database synchronization through change data capture (CDC), and can replicate Salesforce, Dynamics 365, and Business Central data to databases, data lakes, and warehouses. Data Compare helps find mismatches between datasets for comparison and consolidation. Jobs can run on a schedule or in response to events; supported methods include CDC, ELT, ETL, and Reverse ETL. Deployment options include on-premise and cloud-hosted setups. Listed endpoints include SQL Server, SQLite, MySQL, PostgreSQL, Oracle, IBM Db2, MongoDB, Snowflake, AWS Redshift, AWS S3, Azure Synapse, Databricks, and MinIO. Documentation lists Batch API and J2EE Web Server modes, with EXE, Zip, Docker, and AWS Images deployments. A free Developer plan includes two connectors, up to 10,000 records, and up to three objects. A 14-day trial includes plan features and up to two standard connectors. Paid plans require an annual contract, and add-ons may cost extra.

Gluesync replicates data changes in real time across relational and NoSQL databases, event streams and data lakes. Its log-based change data capture reads committed changes from transaction logs, journals or native CDC APIs instead of repeatedly polling full tables. The platform runs on customer infrastructure and supports on-premises, cloud, private-cloud and hybrid deployments. MOLO17 lists more than 31 supported platforms in four categories, with documented integrations including IBM Db2, PostgreSQL, Oracle, MySQL, Snowflake and Google BigQuery. The supported database list also includes systems such as Microsoft SQL Server, MariaDB, Cassandra, Couchbase and Amazon DynamoDB. An extensible API framework allows custom connectors. The web control plane includes visual pipeline orchestration, field functions, custom UDFs, live monitoring and SQL tools; monitoring covers throughput, latency and pipeline health, including from mobile. Listed security measures include TLS/HTTPS/WSS for data streams, AES-256 node-to-node encryption, OIDC, granular role-based access control, audit logging, and Kubernetes-native secrets and network policies. The maker says sensitive data is not persisted within the engine. Pricing is available on request, and a 30-day trial runs on the customer’s infrastructure with enterprise support during the trial. For a proof of concept, the trial page recommends a dedicated host with 8 vCPU, 8 GB RAM (16 GB recommended) and 250 GB disk.