Cloud-Scale Architecture
Striim scales horizontally on in-memory compute with high availability and failover for maximum uptime.
Hevo scales horizontally on Amazon’s AWS cloud.
Striim
Hevo
A unified platform for data integration and streaming that modernizes and integrates industry specific services across millions of customers.
Including:
Fortune 500 companies power their cloud initiatives with Striim
“Our legacy analytics platform used to take an hour per customer data load and weeks for each new deployment. With Striim we are able to transfer operational data to Snowflake in near realtime.”
Prashant Soral,
CTO at Inspyrus
“We chose Striim as it provides continuous access to the data in our MySQL database without impacting its performance, and without taking the data out of the Google Cloud environment.”
Paolo Giangiacomo,
Systems Integration Manager, HomeServe
Striim scales horizontally on in-memory compute with high availability and failover for maximum uptime.
Hevo scales horizontally on Amazon’s AWS cloud.
Striim
Hevo
Striim can be deployed on-premise and in the cloud.
Striim
Hevo
Striim users can build detailed in-flight transformations, data masking, and filtering logic using high-speed SQL queries. Striim scales horizontally with in-memory compute for high performance transformations.
Hevo offers both pre-load (ETL) and post-load (ELT) transformations. Pre-load transformations aren’t designed for real-time data. Post-load transformations (Models and Workflows) allow users to carry out transformations in the destination data warehouse.
Striim
Hevo
Striim offers real-time dashboards visualizing end-to-end data delivery from source to target. Striim matches source and target transactions and alerts users to missing transactions, making it easy to catch issues as they happen. Customers see end-to-end latency under 2 seconds.
Hevo offers a pipeline progress bar and a snapshot of pipeline activity. Can be difficult to debug pipeline issues.
Striim
Hevo
Striim supports data enrichment and normalization using in-memory key-value stores for historic data. This allows you to enrich raw, real-time data with historical aggregates and lookup data.
With Hevo, real-time data enrichment is not possible.
Striim
Hevo
Striim’s cloud partners include Google, Microsoft, AWS, and Snowflake. Striim partners closely with cloud vendors to support a full breadth of endpoints for a variety of strategic use cases. Striim also supports deployment via metered and SaaS marketplace offerings to take advantage of cloud scalability.
No major cloud partnerships have been announced by Hevo.
Striim
Hevo
Striim allows custom alerts on data delivery SLAs, data loss, and user-defined rules.
Hevo offers a limited set of pre-defined alerts.
Striim
Hevo
Striim
Hevo
Striim
Hevo
Striim
Hevo
Striim
Hevo
Striim
Hevo
Striim supports high-performance, E1P log-based CDC for many popular databases including: Oracle, PostgreSQL, MongoDB, MySQL, HPE Nonstop, and SQL Server.
Hevo supports log-based CDC for Oracle, PostgreSQL, MongoDB and MySQL, but not for HPE Nonstop or SQL Server. No mention of high-performance, E1P CDC.
Striim
Hevo
Select from hundreds of templates to simplify building your data flows. A step-by-step wizard will lead you through the process of connecting to your source and target to create a data flow application. You can also create custom data flows from scratch.
Your data flow defines how to collect, process, and deliver data. The simplest data flow just has a source, a stream, and a target. In many cases you will need to perform some processing on your data. Striim enables you to set up continuous SQL queries optimized for streaming, real-time data.
Our built-in dashboards and monitoring enable you to see the state of your data flows in real-time and easily identify any bottlenecks. Striim can also validate that your data has been delivered and provide visibility into the end-to-end lag. This level of visibility is essential for mission-critical systems that may have SLAs regarding how current the data is.
You can also drill down on any of the components in a data flow to see detailed statistics that include read/write rate, lag, latency, CPU usage, and many other metrics. This detailed information can help identify any bottlenecks, and aids in tuning data flows for maximum performance and minimal latency.
Striim allows you to define SQL-based custom alerts so you can stay informed about the status and performance of your data flows.
In the case of errors, or failures, you can also automate workflows to perform corrective actions. By tapping into error or status streams you can trigger compensating data flows to start, or perform other actions to remediate problems.
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