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DBMS > Apache Impala vs. Percona Server for MongoDB vs. Riak TS vs. Splice Machine

System Properties Comparison Apache Impala vs. Percona Server for MongoDB vs. Riak TS vs. Splice Machine

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonPercona Server for MongoDB  Xexclude from comparisonRiak TS  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA drop-in replacement for MongoDB Community Edition with enterprise-grade features.Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KVOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSDocument storeTime Series DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score14.03
Rank#40  Overall
#24  Relational DBMS
Score0.55
Rank#253  Overall
#39  Document stores
Score0.25
Rank#308  Overall
#26  Time Series DBMS
Score0.54
Rank#255  Overall
#116  Relational DBMS
Websiteimpala.apache.orgwww.percona.com/­mongodb/­software/­percona-server-for-mongodbsplicemachine.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.percona.com/­percona-distribution-for-mongodbwww.tiot.jp/­riak-docs/­riak/­ts/­latestsplicemachine.com/­how-it-works
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaPerconaOpen Source, formerly Basho TechnologiesSplice Machine
Initial release2013201520152014
Current release4.1.0, June 20223.4.10-2.10, November 20173.0.0, September 20223.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoGPL Version 2Open SourceOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++ErlangJava
Server operating systemsLinuxLinuxLinux
OS X
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
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.nonono
Secondary indexesyesyesrestrictedyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyes, limitedyes
APIs and other access methodsJDBC
ODBC
proprietary protocol using JSONHTTP API
Native Erlang Interface
JDBC
Native Spark Datasource
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCActionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceJavaScriptErlangyes infoJava
Triggersnonoyes infopre-commit hooks and post-commit hooksyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationselectable replication factorMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesyesYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Immediate Consistency
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono infolinks between datasets can be storedyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infovia In-Memory Engineyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users and rolesnoAccess rights for users, groups and roles according to SQL-standard

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More resources
Apache ImpalaPercona Server for MongoDBRiak TSSplice Machine
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