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DBMS > Apache Impala vs. Riak TS vs. Sphinx vs. Splice Machine vs. Teradata

System Properties Comparison Apache Impala vs. Riak TS vs. Sphinx vs. Splice Machine vs. Teradata

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonRiak TS  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopRiak TS is a distributed NoSQL database optimized for time series data and based on Riak KVOpen source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelRelational DBMSTime Series DBMSSearch engineRelational DBMSRelational DBMS
Secondary database modelsDocument storeDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.20
Rank#319  Overall
#27  Time Series DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score45.33
Rank#21  Overall
#15  Relational DBMS
Websiteimpala.apache.orgsphinxsearch.comsplicemachine.comwww.teradata.com
Technical documentationimpala.apache.org/­impala-docs.htmlwww.tiot.jp/­riak-docs/­riak/­ts/­latestsphinxsearch.com/­docssplicemachine.com/­how-it-worksdocs.teradata.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaOpen Source, formerly Basho TechnologiesSphinx Technologies Inc.Splice MachineTeradata
Initial release20132015200120141984
Current release4.1.0, June 20223.0.0, September 20223.5.1, February 20233.1, March 2021Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2Open SourceOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ErlangC++Java
Server operating systemsLinuxLinux
OS X
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
hosted
Linux
Data schemeyesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesnonoyesyes
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.nonoyes
Secondary indexesyesrestrictedyes infofull-text index on all search fieldsyesyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLSQL-like DML and DDL statementsyes, limitedSQL-like query language (SphinxQL)yesyes infoSQL 2016 + extensions
APIs and other access methodsJDBC
ODBC
HTTP API
Native Erlang Interface
Proprietary protocolJDBC
Native Spark Datasource
ODBC
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesAll languages supporting JDBC/ODBCC 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++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceErlangnoyes infoJavayes infoUDFs, stored procedures, table functions in parallel
Triggersnoyes infopre-commit hooks and post-commit hooksnoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar PartitioningSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication factornoneMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesnoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono infolinks between datasets can be storednoyesyes
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
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnonoAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard

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Apache ImpalaRiak TSSphinxSplice MachineTeradata
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