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DBMS > Apache Impala vs. Microsoft Azure Synapse Analytics vs. Riak TS vs. Sphinx vs. Splice Machine

System Properties Comparison Apache Impala vs. Microsoft Azure Synapse Analytics vs. Riak TS vs. Sphinx vs. Splice Machine

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonRiak TS  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerRiak 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
Score15.06
Rank#39  Overall
#24  Relational DBMS
Score23.95
Rank#30  Overall
#18  Relational DBMS
Score0.28
Rank#308  Overall
#27  Time Series DBMS
Score6.06
Rank#61  Overall
#6  Search engines
Score0.54
Rank#257  Overall
#118  Relational DBMS
Websiteimpala.apache.orgazure.microsoft.com/­services/­synapse-analyticssphinxsearch.comsplicemachine.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.microsoft.com/­azure/­synapse-analyticswww.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 release20132016201520012014
Current release4.1.0, June 20223.0.0, September 20223.5.1, February 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen SourceOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++ErlangC++Java
Server operating systemsLinuxhostedLinux
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.nonono
Secondary indexesyesyesrestrictedyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesyes, limitedSQL-like query language (SphinxQL)yes
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
ODBC
HTTP API
Native Erlang Interface
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC#
Java
PHP
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-reduceTransact SQLErlangnoyes infoJava
Triggersnonoyes infopre-commit hooks and post-commit hooksnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding, horizontal partitioningShardingSharding 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 factoryesselectable 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 ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsno infolinks between datasets can be storednoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes 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 KerberosyesnonoAccess rights for users, groups and roles according to SQL-standard

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More resources
Apache ImpalaMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseRiak TSSphinxSplice Machine
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