What is Mondrian?
It is a Hitachi Group Company, data integration and business analytics company with an enterprise, Online Analytical Processing server (OLAP). Allows business users to analyze large and complex amounts of data in real-time.
Mondrian is a tool in the Big Data Tools category of a tech stack.
Mondrian is an open source tool with 816 GitHub stars and 617 GitHub forks. Here’s a link to Mondrian's open source repository on GitHub
Who uses Mondrian?
4 developers on StackShare have stated that they use Mondrian.
Why developers like Mondrian?
Here’s a list of reasons why companies and developers use Mondrian
Be the first to leave a pro
- Analyze all your data in real-time
- System responds to queries fast enough to allow an interactive exploration of the data
- Brings multidimensional analysis to the masses
- Allowing users to examine business data by drilling and cross-tabulating information.
Mondrian Alternatives & Comparisons
What are some alternatives to Mondrian?
See all alternatives
Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.
Apache Flink is an open source system for fast and versatile data analytics in clusters. Flink supports batch and streaming analytics, in one system. Analytical programs can be written in concise and elegant APIs in Java and Scala.
Presto is an open source distributed SQL query engine for running interactive analytic queries against data sources of all sizes ranging from gigabytes to petabytes.
Hive facilitates reading, writing, and managing large datasets residing in distributed storage using SQL. Structure can be projected onto data already in storage.