Striim’s Latest Releases Boost Cloud Integration, Ease of Use, and Extensibility
Aug. 16, 2018 — In a blog post, which is included in part below, Striim has highlighted the features of its latest releases.
The Striim team has been busy! With a focus on cloud integration and extensibility of the Striim platform, we have delivered two new releases in the last two months. We are excited to share with you what’s new.
In late June 2018, we released version 3.8.4 which brought several features that improve the manageability and the extensibility of the platform, while making it easy for you to offload critical analytics workloads to the cloud. Earlier this month, we released Striim version 3.8.5 which includes a platform as a service (PaaS) offering for real-time data integration to Azure SQL Data Warehouse. In this blog post, you can find an overview of the new features of the latest Striim releases. Let’s start with cloud integration.
Cloud Integration with a Broader Set of Targets
Available as a cloud service, Striim offers continuous real-time data movement with scalability, enabling faster time to market so you can reap the agility and cost-savings benefits of cloud-based analytics. Striim can now deliver real-time data to additional cloud services, such as Azure SQL Data Warehouse, Azure Database for PostgreSQL, Azure Database for MySQL, and Google Cloud SQL. The solutions for Azure SQL DW, Azure SQL DB, Azure HDInsight and Azure Storage are also available as subscription-based services in the Azure Cloud. If you are an Azure user, you can get started with these solutions in minutes.
As you may have read in prior blog posts, Striim is known for its low-impact change data capture (CDC) feature to ingest real-time data from enterprise databases. With the version 3.8.5, we’ve also introduced an Incremental Batch Reader that can collect low-latency data in mini-batch mode from databases that do not support CDC. The source databases for incremental batch loading include Teradata, Netezza, or any other JDBC-compliant database. One prevalent use case for this new feature is enabling a near real-time data pipeline from existing data warehouses to Azure SQL Data Warehouse to ease and accelerate the transition of analytics workloads to the cloud.
With a broad and continually growing set of cloud targets, Striim allows you to create enterprise-grade, real-time data pipelines to feed different layers of your cloud-based solutions such as:
- Analytics services and data warehousing solutions, such as Azure SQL Data Warehouse and Google BigQuery, that directly support end users with timely intelligence
- Data management and analytics frameworks, such as Azure HDInsight, which support interactive analysis or creating machine learning models
- Storage solutions, such as Amazon S3 or Azure Data Lake Storage(ADLS), from on-premises and other cloud-based data sources in real time
- Staging solutions, such as HDFS, S3, and Azure Data Lake Storage, which are used by other cloud services and components
In short: to get the most out of your cloud-based analytics, you need continuous data flows to different components of your architecture. Striim supports all key layers of your cloud-based analytics architecture with enterprise-grade solutions to enable continuous data flows where needed.
To read part two of the blog post, click this link.