Category: Computing & data (Page 47 of 91)

Databricks, the Data and AI company known for their data lakehouse architecture, announced the final closing of their recent Series H funding. Cloud leaders and existing investors Amazon Web Services (AWS), CapitalG, and Microsoft will participate in Databricks’ $1.6 billion round of funding, which puts the company at a $38 billion post-money valuation. The Series H funding will be used to accelerate innovation and adoption of the lakehouse as the data architecture’s popularity across data-driven organizations continues to grow at a rapid pace.

Databricks has a simple and open architecture for data and AI, which brings the reliability, governance, and performance of a data warehouse directly to the data lakes that most organizations already store all of their data in. Rather than being forced to move data out of the data lake, and between various disconnected and legacy systems for different use cases, Databricks customers are building analytics platforms on AWS, Microsoft Azure, and Google Cloud to support every data and analytics workload in a single, unified location.

https://databricks.com/company/newsroom/press-releases/databricks-closes-series-h-with-additional-participation-from-strategic-partners

Tableau, an analytics platform, unveiled new data and analytics platform capabilities. The new enterprise capabilities and new enterprise subscription plans will help customers advance their digital transformations by empowering everyone in an organization with trusted and governed data.

• Managing the data chaos and enabling data governance. New capabilities are making data challenges easier to manage, scale, and trust
  • Data Prep: Reduce loads/costs of server resources automatically and generate rows to more map out trends in data
  • Governance: Help ensure/maintain data quality by alerting you of any potential issues and provide easier visibility into the type of data you have and where it came from
  • Centralized row level security: Increased flexibility and segmentation by allowing Tableau administrators to centrally configure which users and groups have access to which slices of data configure access.
• Ensuring analytics scales with enterprise demand
  • Enterprise reference architecture: Enterprise Deployment Guidelines (EDG) provides the Tableau reference architecture to enterprises to achieve requirements around availability, scalability and security.
  • Dynamic Scaling: Helps enterprises appropriately resource their deployment and ensures enough containers are available during peak demand times and scale down during low demand times.
  • Resource Management: IT teams can better optimize the performance of Tableau Server by defining application resource limits.

https://www.tableau.com/products/our-platform

The Apache Drill Project announced the release of Apache Drill v1.19, the schema-free Big Data SQL query engine for Apache Hadoop, NoSQL, and Cloud storage. v1.19 reflects more than 100 changes, improvements, and new features.

An “SQL-on-Hadoop” engine, Apache Drill is easy to deploy, able to process trillions of records, and scalable from a single laptop to a 1000-node cluster. With its schema-free JSON model, Drill is able to query complex semi-structured data in situ without requiring users to define schemas or transform data. It provides plug-and-play integration with existing Hive and HBase deployments, and is extensible out-of-the-box to multiple data sources, such as S3 and Apache HDFS, HBase, and Hive. Additionally, Drill can directly query data from REST APIs to include platforms like SalesForce and ServiceNow. 

Drill supports the ANSI SQL 2003 standard syntax ecosystem as well as dozens of NoSQL databases and file systems, including Apache HBase, MongoDB, Elasticsearch, Cassandra, REST APIs, , HDFS, MapR-FS, Amazon S3, Azure Blob Storage, Google Cloud Storage, NAS, local files, and more. Drill leverages familiar BI tools (such as Apache Superset, Tableau, MicroStrategy, QlikView and Excel) as well as data virtualization and visualization tools, and runs interactive queries on Hive tables with different Hive metastores.

http://drill.apache.org

Confluent, Inc. announced the Confluent Q3 ʼ21 Release, with features that help organizations share data between different environments, integrate with business-critical applications, and store data for digital customer experiences and data-driven backend operations.

As a part of the Q3 ʼ21 Release, ksqlDB pull queries are now generally available in Confluent Cloud. Together with push queries, ksqlDB enables a broad class of end-to-end stream processing workloads without the need to work across multiple systems to build streaming applications.

Confluent has expanded its library of managed Kafka. The Salesforce Platform Events Source connector enables organizations to unlock customer data and share it with downstream data warehouses and applications. The Azure Cosmos DB Sink connector helps companies migrate to a modern, cloud-native database to enable high performance and automatic scaling, unlocking real-time use cases.

Confluent re-architected Kafka to work in the cloud. Infinite Storage is now generally available for Google Cloud, after initially launching for AWS. Organizations can now retain all the real-time and historical data they need without pre-provisioning additional infrastructure or running the risk of paying for unused storage.

https://www.confluent.io/