Big Data

Connect to big data without limitations.

Screenshot showing a user selecting a Hadoop data source in the MicroStrategy interface.

Many organizations choose Hadoop to store and process big data. With MicroStrategy, users can leverage information such as click stream, web and call center logs, and ID scans without limitation. Whether it’s a simple spreadsheet or a dispersed Hadoop Distributed File System (HDFS), users can easily connect to their data without having to rely on IT. Organizations can also operationalize data lakes and deliver a single version of the truth with the industry’s most secure, governed enterprise analytics platform. MicroStrategy brings big data to your Intelligent Enterprise.

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Explore big data on your own.

MicroStrategy lets business users and departmental teams quickly connect to, prepare, and visualize information stored in big data environments. Users can also generate multi-pass SQL, blend data using our powerful push-down architecture, and seamlessly drill across multiple sources using dynamic sourcing capabilities, all while leveraging the power of Hadoop clusters.

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Screenshots of three visualizations that use big data as sources.

Operationalize your enterprise data lake.

MicroStrategy’s open architecture allows organizations to seamlessly leverage their existing big data investments. By partnering with leading cloud infrastructure providers like Amazon Web Services (AWS), Google Cloud, and Microsoft Azure, MicroStrategy helps organizations operationalize their data lakes and bring powerful enterprise analytics to the world of big data.

  • Amazon S3
  • Amazon Redshift
  • Amazon EMR
  • Amazon Athena
  • Amazon Aurora MySQL
  • Google BigQuery
  • Google Analytics
  • Google Drive
  • Microsoft SQL Server
  • Microsoft Azure SQL Data Warehouse
  • Microsoft Azure Cosmos DB
  • Microsoft SQL Server Analysis Services
  • Microsoft Azure HDInsight
  • Microsoft Access
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Work with any flavor of Hadoop.

SQL on Hadoop continues to be the most popular way for organizations to run queries on data stored in HDFS. With a wide range of out-of-the-box connectors, MicroStrategy enables organizations to leverage their existing investments in big data technology and directly connect to Hadoop distributors like Cloudera, Hortonworks, MapR, IBM BigInsights, and Pivotal. Organizations can leverage all SQL on Hadoop technologies, including Cloudera Impala, MapR Drill, Apache Spark, Pivotal HAWQ, and Facebook Presto to support interactive queries.

Cloudera
Hortonworks
MAPR
IBM InfoSphere BigInsights
Pivotal
Apache HAWQ
Presto
Cloudera Impala
Apache Spark
Apache Drill

MicroStrategy Analytics Platform

Batch SQL

  • Cloudera
  • MapR
  • Hortonworks
  • Amazon EMR

Interactive SQL

  • Apache Drill
  • Cloudera Impala
  • Google BigQuery
  • Pivotal Hawq
  • IBM BigInsights
  • Apache Spark
  • Facebook Presto

No SQL

  • Apache HBase
  • Cassandra
  • MongoDB
  • MarkLogic

Search

  • Apache Solr
  • Splunk

Native Access

  • MicroStrategy Hadoop Gateway

Distributed File Systems (HDFS, Amazon S3, GFS…)

Adaptive data connectivity

Enterprise analytics platforms need to be able to keep up with the rapidly changing big data landscape and seamlessly adapt to new technologies and data storage paradigms. The MicroStrategy platform is highly flexible, so organizations can easily move legacy data assets to Hadoop or switch to cloud-based data storage without impacting existing reports, dashboards, or applications.

Connect to NoSQL databases

Organizations often use NoSQL databases to store semi-structured data that is well suited for real-time analysis, transactional analysis, and more. MicroStrategy provides direct connectivity to NoSQL databases like MongoDB, MarkLogic, Apache HBase, and Cassandra.

Natively connect to HDFS

The MicroStrategy Hadoop Gateway makes it easy for organizations to tap into their Hadoop assets. With Spark, MicroStrategy can improve scalability and performance when accessing data directly from HDFS. What’s more, in self-service scenarios, end users have the power to easily filter and aggregate data in the HDFS cluster so they only access relevant information, resulting in greater flexibility and better performance.

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