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DBMS > Apache Impala vs. Microsoft Access vs. Riak TS vs. Sphinx vs. Splice Machine

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

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonRiak TS  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)Riak 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 Spark
Primary database modelRelational DBMSRelational DBMSTime Series DBMSSearch engineRelational 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
Score105.40
Rank#11  Overall
#8  Relational DBMS
Score0.25
Rank#308  Overall
#26  Time Series DBMS
Score6.03
Rank#60  Overall
#6  Search engines
Score0.54
Rank#255  Overall
#116  Relational DBMS
Websiteimpala.apache.orgwww.microsoft.com/­en-us/­microsoft-365/­accesssphinxsearch.comsplicemachine.com
Technical documentationimpala.apache.org/­impala-docs.htmldeveloper.microsoft.com/­en-us/­accesswww.tiot.jp/­riak-docs/­riak/­ts/­latestsphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaMicrosoftOpen Source, formerly Basho TechnologiesSphinx Technologies Inc.Splice Machine
Initial release20131992201520012014
Current release4.1.0, June 20221902 (16.0.11328.20222), March 20193.0.0, September 20223.5.1, February 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infoBundled with Microsoft OfficeOpen SourceOpen Source infoGPL version 2, commercial licence 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++C++ErlangC++Java
Server operating systemsLinuxWindows infoNot a real database server, but making use of DLLsLinux
OS X
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeyesyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesnonoyes
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
Secondary indexesyesyesrestrictedyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infobut not compliant to any SQL standardyes, limitedSQL-like query language (SphinxQL)yes
APIs and other access methodsJDBC
ODBC
ADO.NET
DAO
ODBC
OLE DB
HTTP API
Native Erlang Interface
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
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++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes infosince Access 2010 using the ACE-engineErlangnoyes infoJava
Triggersnoyes infosince Access 2010 using the ACE-engineyes infopre-commit hooks and post-commit hooksnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneselectable replication factornoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyesnoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno infolinks between datasets can be storednoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infobut no files for transaction loggingnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyes infobut no files for transaction loggingyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
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 Kerberosno infoa simple user-level security was built in till version Access 2003nonoAccess rights for users, groups and roles according to SQL-standard

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More resources
Apache ImpalaMicrosoft AccessRiak TSSphinxSplice Machine
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