Stelo + Snowflake

No. Stelo offers simple installation and GUI-based replication. Our user-friendly, browser-based GUI does not require a programming background to set up or operate. The easy-to-use interface comes standard across all Stelo solutions for snapshot, incremental, and bi-directional replication. Once running, Stelo reliably operates in the background without needing dedicated engineering support to maintain and manage.

Stelo’s typical, near real-time latency rate is under 1 second. Once replication source and destination databases have been defined, Stelo uses change data capture techniques to capture and apply only change data. Our multithreaded processing is far more efficient than other replication tools on the market, not only to provide near real-time data availability, but also best in terms of reliability and robustness. Stelo’s custom technology blurs the overhead of the WAN connection and effectively delivers near real-time (under 1 second) replication, regardless of whether it's going into cloud or on-premise locations. If your use-case requires sub-second latency at all times, we will size the replication instance according to your high-water mark of DML activity to ensure near real-time data availability.

Yes. Stelo can handle large-scale data transfers replication with sub-second latency. A single instance can support multiple sources and destinations without additional licensing. The Stelo model is independent of the number of cores of either the source or destination—so you only pay for the capacity required to support the transaction connections. This cost-efficient method merges source data flows into one stream, and then is applied to any number of subscribing destinations. Stelo delivers enterprise-level performance without enterprise-level cost.

Analyzing a company’s ongoing transactional or operational data can provide key insights that drive business decisions and processes. Many companies offload these operations to other databases, data warehouses, or data lakehouses to reduce source system load and save costs. However, replicating dynamic data from multiple source databases to one or more destination application requires real-time change data capture (CDC) to ensure all updates are automatically and reliably reflected. In other words, business insights are only effective if data changes are accurately captured and delivered across the connected databases over time.

CDC is typically the first stage in the data ingestion process and represents the “extraction phase” in the ETL and ELT approaches. CDC strategies often demand a tradeoff between latency tolerance and change volume requirements, but Stelo’s approach provides the ideal balance between fast, high-volume performance and lossless data capture. Our process can simultaneously propagate a source system’s information changes and structure updates to destination platforms so that the data appears in the correct sequence at the same time. In addition, the cost-efficient method merges incoming data flows into one stream, as opposed to using many streams, which becomes expensive. Read our blog posts about moving data into delta lakes or using delta lakes for future scalability to learn more.