Cloud-Scale Architecture
Striim scales horizontally on in-memory compute with failover and high availability for maximum uptime.
StreamSets also scales horizontally and offers failover and high availability.
Striim
StreamSets
Why Choose Striim vs. StreamSets?
- Built for mission-critical enterprise workloads
- End-to-end latency less than 2 seconds
- Transform, enrich, and analyze your data on the fly
Fortune 500 companies power their cloud initiatives with Striim
Companies Choose Striim for Scalable, Real-Time Replication
“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 vs. StreamSets Feature Comparison
Enables Hybrid-Cloud Use Cases
Striim can be deployed on-premise and in the cloud.
StreamSets can also be deployed on-premise and in the cloud.
Striim
StreamSets
Exactly Once Data Delivery Guarantee
Striim’s advanced checkpointing capabilities ensure that no events are missed or processed twice.
StreamSets offers a choice of “At Least Once” or “At Most Once” data delivery guarantees which means that data can be either lost or duplicated, depending on which option is chosen.
Striim
StreamSets
High-Performance Change Data Capture (CDC)
Striim supports high-performance, E1P log-based CDC for many popular databases including: Oracle, PostgreSQL, MongoDB, MySQL, HPE Nonstop, and SQL Server. Built by the executive & technical team from GoldenGate Software, Striim brings decades of experience in mission-critical enterprise workloads.
StreamSets offers CDC from popular databases, but there is no mention of high-performance E1P CDC.
Striim
StreamSets
Detailed, Real-Time Data Visualization Dashboards
Striim offers detailed and customizable 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 identify issues as they occur. Striim offers data delivery and latency SLAs. Customers see end-to-end latency under 2 seconds.
StreamSets allows users to monitor jobs with a “Realtime Summary” that includes Record Count, Record Throughput, and Runtime statistics. They provide error messages and logs which can be time-intensive to scan through in the event of data loss or data lag scenarios.
Striim
StreamSets
Custom Alerts
Striim allows custom alerts on data delivery SLAs, data loss, and user-defined rules. Striim’s custom alerts are created using streaming SQL.
StreamSets also allows the creation of custom alerts using the StreamSets expression language (based on JSP 2.0 expression language).
Striim
StreamSets
Automated Corrective Actions
Striim users can create custom workflows to perform corrective actions in the event of errors or failures. By tapping into error or status streams users can trigger compensating data flows, or perform other actions to remediate problems.
Striim
StreamSets
Real-Time Data Enrichment
Striim supports data enrichment and normalization using in-memory key-value stores for historic data. This allows users to enrich raw, real-time data with historical aggregates and lookup data.
Striim
StreamSets
Real-time Transformations
Striim users use streaming SQL for in-flight transformations, correlation, aggregation, masking, filtering, and analytics. Striim scales horizontally with in-memory compute for high performance transformations.
StreamSets Transformer leverages Apache Spark to allow users to perform stream processing and machine learning operations.
Striim
StreamSets
Cloud Partnerships
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.
StreamSets cloud partners include Google, AWS, and Microsoft.
Striim
StreamSets
Data Sources: Cloud + On-Premise
Databases and Data Warehouses
Striim
StreamSets
Data Sources: IoT Devices
Striim
StreamSets
Data Sources: Kafka
Striim
StreamSets
Data Targets: Cloud Data
Warehouses and Databases
Striim
StreamSets
Data Targets: Files and Logs,
Messaging Systems, Big Data
Striim
StreamSets
Striim offers a modern data platform that's both powerful and easy to use
Create data flows with a few clicks
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.
Process your data with real-time SQL queries
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.
Monitor your data flow in real-time
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.
Set alerts and create workflows to take corrective action
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.
” Striim gives us a single source of truth across domains and speeds our time to market delivering a cohesive experience across different systems. “
Neel Chinta, IT Manager at Macy’s
Sources
Microsoft SQL Server
MongoDB
MySQL
Oracle
PostgreSQL
Salesforce
Targets
Azure Synapse Analytics
Databricks
Google BigQuery
Kafka
PostgreSQL
Snowflake
Helpful how-to guides
We've prepared a few articles to help you get started
Streaming Data Integration
February 17, 2023
Streaming Data Integration
February 15, 2023
