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.
Automated, fully managed SaaS solution for streaming data pipelines for BigQuery.
Key Integrations:
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:
Striim can connect hundreds of source and target combinations. View a complete list.
Read the latest blogs from our experts
Search all our latest recipes, videos, podcasts, webinars and ebooks
Find the latest webinars, online, and face-to-face events
Stay up to date on new product updates & join the discussion.
Let Striim’s services and support experts bring your Data Products to life
Find the latest technical information on our products
Learn all about Striim, our heritage, leaders and investors
Looking to work for Striim? Find all the available job options
See how our customers are implementing our solutions
Find out more about Striim's partner network
Find all the latest news about Striim
Connect with the experts at Striim
According to a Gartner prediction, only 20% of data analytics projects will deliver business outcomes. Indeed, given that the current data architectures are not well
What is Data Replication Data Replication Benefits Data Replication Challenges Data Replication Methods Log-Based Incremental Replication Key-Based Incremental Replication Full Table Replication Snapshot Replication Transactional
Since announcing our Series C fundraising led by Goldman Sachs we doubled down on our mission to enable companies to power their decisions in real-time,
Consider the following stats: the 2020 Vena Industry Benchmark Report found that 57% of finance teams see data silos as a challenge; Treasure Data’s Customer
According to a study by Experian, 98% of companies rely on data to enhance their customer experience. In today’s data age, getting data analytics right
We are excited to announce our new Striim Database Migration Service, StreamShift that provides native integration with Microsoft Azure Cosmos DB. We have worked hard to resolve any pain
If you’re comparing DataOps vs DevOps for a practical digital transformation approach, you’re engaging in the wrong debate. Sure DevOps has revolutionized how companies deliver
Both data warehouses and data lakes have been serving companies well for a long time. Despite their pros, each also has its limitations. That’s why
Data has become one of the most valuable assets in modern times. As more companies rely on insights from data to drive critical business decisions,
As a unified data streaming and integration company, the Striim platform sits at the heart of our customers’ data architecture. It is crucial that our
New release focuses on secure, automated multi cloud data pipelines to stream mission critical business events in real time Palo Alto, Calif. — December 8,
Data warehouses allow businesses to find insights by storing and analyzing huge amounts of data. Over the last few years, Snowflake, a cloud-native relational data
