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DBMS > Apache Impala vs. Heroic vs. Percona Server for MongoDB vs. SingleStore vs. Splice Machine

System Properties Comparison Apache Impala vs. Heroic vs. Percona Server for MongoDB vs. SingleStore vs. Splice Machine

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonHeroic  Xexclude from comparisonPercona Server for MongoDB  Xexclude from comparisonSingleStore infoformer name was MemSQL  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchA drop-in replacement for MongoDB Community Edition with enterprise-grade features.MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table typeOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSTime Series DBMSDocument storeRelational DBMSRelational DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
Time Series DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.63
Rank#40  Overall
#24  Relational DBMS
Score0.13
Rank#335  Overall
#29  Time Series DBMS
Score0.50
Rank#250  Overall
#39  Document stores
Score4.02
Rank#74  Overall
#39  Relational DBMS
Score0.54
Rank#244  Overall
#114  Relational DBMS
Websiteimpala.apache.orggithub.com/­spotify/­heroicwww.percona.com/­mongodb/­software/­percona-server-for-mongodbwww.singlestore.comsplicemachine.com
Technical documentationimpala.apache.org/­impala-docs.htmlspotify.github.io/­heroicdocs.percona.com/­percona-distribution-for-mongodbdocs.singlestore.comsplicemachine.com/­how-it-works
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaSpotifyPerconaSingleStore Inc.Splice Machine
Initial release20132014201520132014
Current release4.1.0, June 20223.4.10-2.10, November 20178.5, January 20243.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0Open Source infoGPL Version 2commercial infofree developer edition availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC++C++, GoJava
Server operating systemsLinuxLinuxLinux info64 bit version requiredLinux
OS X
Solaris
Windows
Data schemeyesschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.nononono
Secondary indexesyesyes infovia Elasticsearchyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoyes infobut no triggers and foreign keysyes
APIs and other access methodsJDBC
ODBC
HQL (Heroic Query Language, a JSON-based language)
HTTP API
proprietary protocol using JSONCluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC
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
Bash
C
C#
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-reducenoJavaScriptyesyes infoJava
Triggersnonononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infohash partitioningShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesSource-replica replicationSource-replica replication infostores two copies of each physical data partition on two separate nodesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyesno infocan define user-defined aggregate functions for map-reduce-style calculationsYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes infoAll updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes infovia In-Memory Engineyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users and rolesFine grained access control via users, groups and rolesAccess rights for users, groups and roles according to SQL-standard

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More resources
Apache ImpalaHeroicPercona Server for MongoDBSingleStore infoformer name was MemSQLSplice Machine
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