Data Management Systems
Data Management Systems
Our (Big) Data Management Systems link sheet is a permanent resource that will be updated on a bi-weekly basis that will provide an overview of NoSQL and SQL DBMS.
Join the DZone community and get the full member experience.Join For Free
Hortonworks Sandbox for HDP and HDF is your chance to get started on learning, developing, testing and trying out new features. Each download comes preconfigured with interactive tutorials, sample data and developments from the Apache community.
This linksheet is part of a series of source compilations covering a wide variety of topics. Our Data Management Systems linksheet is a permanent resource that will be updated on a bi-weekly basis that will provide an overview of what types of data management systems exist, organized by their engine type, with brief descriptions. Unsure of what type of management system is right for your data needs, or thinking of making a switch? Here's a cultivated list of NoSQL and SQL DBMS types.
Supports the table model for data. Relational database management systems (RDBMS) are powerful for processing and storing data, set in a fixed format with columns and tables due to its relation schema. Commonly used for finances, manufacturing/logistics and personnel data. While not as flexible as NoSQL databases, an RDBMS is easy to use and understand.
- Oracle db-engines.com has consistently ranked Oracle as the number one engine, overtaking not only its SQL counterparts but its NoSQL competitors as well.
- MySQL - open-source and the favorite of Facebook, Google and Zappos.
SQL Server- Microsoft’s server with in-memory performance.
- PostreSQL- open-source, object-relational DBMS.
DB2- IBM’s database, available on a wide variety of platforms.
Called “Key-Value” due to their storage of keys and values. A value can only be retrieved with a key, and thus key-value stores are not necessarily optimal for complex applications, yet they are still powerful and have their influence in the roots of document and wide column stores.
Redis- open-source and BSD licensed with an in-memory dataset and the ability to run atomic operations.
Memcached - described as an “in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.”
Amazon DynamoDB - considered a multi-model database, DynamoDB is cloud-based and capable of also supporting document stores.
Riak - Basho’s database that comes as Riak KV (Distributed NoSQL Database) and Riak S2 (Object Storage). Integrated with Apache Spark, Solr and Redis.
Ehcache - a full-featured Java Database.
A document store, or document-oriented database, are schema-free, allowing for different data to possess different structures, support for arrays, and nested records. Commonly uses JSON. Document stores also extract metadata for optimization, are flexible to deal with change, and tend to be smaller in size as a result.
- MongoDB - MongoDB has held its rank in the top five DBMS on db-engines.com for a while now. It’s fast-growing, scalable and agile.
Couchbase - not to be confused with CouchDB, Couchbase also offers a mobile version.
MarkLogic - a NoSQL DBMS made for the enterprise.
RavenDB - a powerful open-source NoSQL database for .NET.
Opinions expressed by DZone contributors are their own.