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IBM Db2 Big SQL

SQL-on-Hadoop-Anwendung für Big-Data-Analytics

The 15 most significant big data fabric vendors

Read the Forrester Wave Report

Überblick

IBM Db2 Big SQL is a SQL engine for Apache Hadoop that concurrently accesses Apache Hive, Apache HBase, and Apache Spark using a single database connection.

A modern data platform, Db2 Big SQL and HDP provide flexibility, elasticity and production grade performance with container technologies on fine-tuned systems both on premises and in the cloud. This flexibility enables organizations to have a seamless hybrid implementation ingest, high availability and disaster recovery.

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IBM Db2 Big SQL

Vorteile

Port applications with ease

DB2 Big SQL and HDP architecture is based on many years of experience managing large-scale Hadoop clusters within complex data environments. DB2 Big SQL is the first and only SQL-on-Hadoop solution to understand commonly used SQL syntax from other vendors and products such as Oracle, IBM Db2 and IBM Netezza®. This makes it easier to:

  • Migrate existing applications without major rewrites
  • Be compatible with Oracle, Db2, and Netezza SQL syntax
  • Port applications for business intelligence tools including Cognos and Tableau
Solution Sheet: IBM Db2 Big SQL Solution Sheet
Blog: Teaming on Data: IBM and Hortonworks Broaden Relationship
Drive down costs

While Hadoop is highly scalable, the Db2 Big SQL advanced cost-based optimizer and massively parallel processing (MPP) architecture can run queries smarter, not harder. It supports more concurrent users and more complex SQL with less hardware compared to other SQL solutions for Apache Hadoop. Db2 Big SQL makes it easier to modernize your EDW and realize costs savings faster. With Db2 Big SQL, you can:

  • Offload costly ETL processing to free your EDW to perform analytics and operations
  • Refine new data sources for analytical context
  • Archive data away from EDW to reduce costs
Blog: Top Questions – Modernize Your Existing EDW with IBM Db2 Big SQL & Hortonworks Data Platform
Slideshare: Modernize your Existing EDW with IBM Db2 Big SQL and HDP
Integrated and seamless

Db2 Big SQL and HDP fit within your larger data fabric. Both architectures are based on many years of experience managing large-scale Hadoop clusters within complex data environments. Configurations are available to perform on virtually every type of Hadoop workload. Other features include:

  • Tooling to query Apache Hive, Apache Spark and Apache HBase data from a single SQL engine
  • Federating your data behind one SQL engine using connectors to Teradata, Oracle, and Db2
  • Combining data on Hadoop with data on other non-Hadoop data sources
Webinar: Making Enterprise Big Data Small with Ease
Deliver high performance and concurrency

Db2 Big SQL supports virtually all forms of data, batch and real-time processing, with unmatched scalability and performance. Unlock Hadoop data with analytics tools of choice and achieve high concurrency for business intelligence workloads by executing complex queries smarter. Use less memory and CPU compared to other SQL solutions for Hadoop.

DB2 Big SQL enables deeper integration with Apache Spark than other SQL-on-Hadoop technologies, enabling new use cases and delivers advanced row and column security: The integration of Db2 Big SQL and Spark enhances “shopping for data” security. Sensitive attributes can be masked by default with no backdoors to the data, which empowers self-service access to data in a safe and governed manner.

Blog: Db2 Big SQL: SQL on Apache Hadoop Across the Enterprise