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DBMS > Apache Impala vs. Rockset vs. Splice Machine

System Properties Comparison Apache Impala vs. Rockset vs. Splice Machine

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonRockset  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA scalable, reliable search and analytics service in the cloud, built on RocksDBOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSDocument storeRelational DBMS
Secondary database modelsDocument storeRelational DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.79
Rank#211  Overall
#35  Document stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteimpala.apache.orgrockset.comsplicemachine.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.rockset.comsplicemachine.com/­how-it-works
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaRocksetSplice Machine
Initial release201320192014
Current release4.1.0, June 20223.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++Java
Server operating systemsLinuxhostedLinux
OS X
Solaris
Windows
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyesdynamic typingyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nono infoingestion from XML files supported
Secondary indexesyesall fields are automatically indexedyes
SQL infoSupport of SQLSQL-like DML and DDL statementsRead-only SQL queries, including JOINsyes
APIs and other access methodsJDBC
ODBC
HTTP RESTJDBC
Native Spark Datasource
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCGo
Java
JavaScript (Node.js)
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyes infoJava
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic shardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users and organizations can be defined via Rockset consoleAccess rights for users, groups and roles according to SQL-standard

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More resources
Apache ImpalaRocksetSplice Machine
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