A fully managed SaaS solution that enables infinitely scalable unified data integration and streaming.
On-premise or in a self-managed cloud to ingest, process, and deliver real-time data.
Seamlessly connect legacy systems to a any modern, hybrid environment
Transform your business with highly responsive digital supply chains and operations powered by real-time data streaming.
Build a global and agile data environment that can track, analyze, and govern data across applications, environments, and users
Transition from reliance on monolithic applications to operating on a modern distributed architecture
Improve the customer journey and use real-time insights to provide a personalized experience
Infuse real-time analytics into every decision you make
Deliver real-time data to AWS, for faster analysis and processing.
Unify data on Google Cloud and power real-time data analytics in BigQuery.
Quickly move data to Microsoft Azure and accelerate time-to-insight with Azure Synapse Analytics and Power BI.
Unleash the power of Databricks AI/ML and Predictive Analytics.
Fulfill the promise of the Snowflake Data Cloud with real-time data.
A unified platform for data integration and streaming that modernizes and integrates industry specific services across millions of customers.
Including:
Flexible Models for Every Business.
Striim can connect hundreds of source and target combinations. View a complete list.
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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.
Fivetran’s scalability is a black box. Unclear if workloads can scale based on data volume. Striim has demonstrated faster performance using multiple nodes and parallel data processing that the user can scale up or down based on their requirements.
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Striim can be deployed on-premise and in the cloud.
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Striim supports long-running transactions with no downtime.
Fivetran will automatically force a re-sync in the event of any unexpected data changes. This can cause hours to days of downtime in the case of large production databases.
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Striim is a modern, real-time ETL solution. Striim users can build detailed in-flight transformations, data masking, filtering logic using high-speed SQL queries. Striim scales horizontally with in-memory compute for high performance transformations.
Fivetran keeps pre-load data processing to a minimum (data is normalized, cleaned, sorted, and de-duplicated). They offer SQL and dbt-based post-load transformations.
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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. Striim offers data delivery and latency SLAs. Customers see end-to-end latency under 2 seconds.
Fivetran does not offer real-time data visualization dashboards with visibility into end-to-end latency. However, their Enterprise plan does guarantees a 5-minute maximum sync frequency and includes data delivery SLAs.
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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.
Fivetran does not support real-time data enrichment.
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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.
Fivetran offers limited technical integration with cloud partners.
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Striim allows custom alerts on data delivery SLAs, data loss, and user-defined rules.
Fivetran offers predefined alerts and the ability to view logs generated by connectors.
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Striim supports high-performance, E1P log-based CDC for many popular databases including: Oracle, PostgreSQL, MongoDB, MySQL, HPE Nonstop, and SQL Server. E1P, high performance CDC is a requirement for mission-critical workloads.
Fivetran supports CDC for databases like Oracle and SQL Server, but there is no mention of E1P, high-performance CDC.
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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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