Striim Version 3.10.1 Includes Expanded Support for Cloud Targets, Including Snowflake Partner Connect, and
Google BigQuery Streaming API, Now Includes Schema Conversion and End-To-End Lag Monitoring,
and Simplifies Working with Complex Data
PALO ALTO, CA – July 10, 2020 – Striim, provider of an enterprise-grade platform for streaming cloud migration and cloud integration solutions, has introduced a broad set of enhancements to its on-premise and cloud marketplace offerings that adds additional cloud targets, provides more detailed visibility into on-going data movement, further enhances ease-of-use, and ensures on-going support for major enterprise data sources.
Key Features released in Striim 3.10.1 are directly available through Snowflake Partner Connect to enable rapid movement of enterprise data into Snowflake. Striim 3.10.1. also introduces support for the Google BigQuery Streaming API, optimizes integrating real-time change data into Snowflake and Azure Synapse, and adds support for Parquet in Cloud Data-Lake solutions.
“In today’s challenging business environment, cloud adoption initiatives have become the number one priority for many organizations looking to optimize their operations, enhance their customers’ online experience, and gain the real-time insights required for digital transformations,” said Alok Pareek, founder and EVP of Products at Striim. “With this release, Striim further simplifies this process through our dedicated support for technologies required by customers undertaking online cloud migrations and investing in cloud analytics.”
Striim on Snowflake Partner Connect
From Snowflake Partner Connect, customers can launch a trial Striim Cloud instance directly as part of the Snowflake on-boarding process from the Snowflake UI and load data, optionally with change data capture, directly into Snowflake from any of our supported sources.
Expanded Support for Cloud Targets to Further Enhance Cloud Adoptions
The Striim platform has been chosen as a standard for our customers’ cloud adoption use-cases partly because of the wide range of cloud targets it supports. Striim provides integration with databases, data warehouses, storage, messaging systems and other technologies across all three major cloud environments. To further enhance this key capability, the following features have been added in the 3.10.1 release:
- Support for the Google BigQuery Streaming API, enabling real-time analytics in BigQuery on large scale data within seconds, as well as helping with quota issues than can be faced by high volume customers
- Optimized delivery to Snowflake and Azure Synapse that facilitates compacting multiple operations on the same data to a single operation on the target resulting in much lower change volume
- Delivery to MongoDB cloud and Mongo DB API for Azure Cosmos DB
- Delivery to Apache Cassandra, DataStax Cassandra, and Cassandra API for Azure Cosmos DB
- Support for delivery of data in Parquet format to Cloud Storage and Cloud Data Lakes to further support cloud analytics environments
Schema Conversion to Simplify Cloud Adoption Workflows
As part of many cloud migration or cloud integration use-cases, especially during the initial phases, developers often need to create target schemas to match those of source data. Striim adds the capability to use source schema information from popular databases such as Oracle, SQL Server, and PostgreSQL and create appropriate target schema in cloud targets such as Google BigQuery, Snowflake and others. Importantly, these conversions understand datatype and structure differences between heterogeneous sources and targets and act intelligently to spot problems and inconsistencies before progressing to data movement.
Enhanced Monitoring, Alerting and Diagnostics
On-going data movement between on-premise and cloud environments for migrations, or powering reporting and analytics solutions, are often part of an enterprise’s critical applications. As such they demand deep insights into the status of all active data flows. Striim 3.10.1 adds the capability to inherently monitor data from its creation in the source to successful delivery in a target, generate detailed lag reports, and alert on situations where lag is outside of SLAs. In addition, this release provides detailed status on checkpointing information for recovery and high availability scenarios, with insight into checkpointing history and currency.
Simplifies Working with Complex Data
As customers work with heterogeneous environments and adopt more complex integration scenarios, they often have to work with complex data types, or perform necessary data conversions. While always possible through user defined functions, this release adds multiple commonly requested data manipulation functions out of the box. This simplifies working with JSON data and document structures, while also facilitating data cleansing, and regular expression operations.
On-Going Support for Enterprise Sources
As customers upgrade their environments, or adopt new technologies, it is essential that their integration platform keeps pace. In Striim 3.10.1 we extend our support for the Oracle database to include Oracle 19c, including change data capture, add support for schema information and metadata for Oracle GoldenGate trails, and certify our support for Hive 3.1.0
For more information on Striim version 3.10.1, please read the related blog post, “Striim 3.10.1 Further Speeds Cloud Adoption,” details on Snowflake Partner Connect are explained in this blog post, “Continuous Data Integration for Snowflake with Striim on Partner Connect,” or contact us for a brief technical walkthrough.
About Striim
The Striim® platform is an enterprise-grade stream data integration solution for moving data in real time to the cloud and other targets. Striim makes it easy to continuously ingest high volumes of streaming data from diverse sources (both on-premises and in the cloud) and provide stream processing and transformations to support cloud adoption, and multi- and hybrid cloud infrastructures, as well as Kafka, Hadoop, and NoSQL integrations. Striim can continuously collect data from enterprise databases (using non-intrusive change data capture), log files, cloud applications, messaging systems, and sensors, and deliver to virtually any target on-premises or in the cloud with sub-second latency. For more information, visit www.striim.com, read our blog at www.striim.com/blog, follow @striimteam, or download the Striim platform.
For more information, press only:
Steve Wilkes
Striim
(650) 241-0680
press@striim.com
