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DBMS > Impala vs. Sphinx vs. Splice Machine

System Properties Comparison Impala vs. Sphinx vs. Splice Machine

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Editorial information provided by DB-Engines
NameImpala  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopOpen 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 DBMSSearch engineRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score15.66
Rank#37  Overall
#22  Relational DBMS
Score6.34
Rank#60  Overall
#7  Search engines
Score0.79
Rank#190  Overall
#93  Relational DBMS
Websitewww.cloudera.com/­products/­open-source/­apache-hadoop/­impala.htmlsphinxsearch.comsplicemachine.com
Technical documentationdocs.cloudera.com/­documentation/­enterprise/­latest/­topics/­impala.htmlsphinxsearch.com/­docsdoc.splicemachine.com
DeveloperClouderaSphinx Technologies Inc.Splice Machine
Initial release201320012014
Current release3.3.0, August 20193.2.1, January 20202.0
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++Java
Server operating systemsLinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesnoyes
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.no
Secondary indexesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language (SphinxQL)yes
APIs and other access methodsJDBC
ODBC
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC++ 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-reducenoyes infoJava
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding 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 factornoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyes 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 KerberosnoAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
ImpalaSphinxSplice Machine
Specific characteristicsTHE ONLY SCALE-OUT SQL RDBMS WITH BUILT-IN MACHINE LEARNING For data-rich, real-time...
» more
Competitive advantagesOperational Workloads: Full ACID support with high performance at scale Multi-row...
» more
Typical application scenariosNew AI/ML and IoT Applications Data Warehouse Offloads Application Modernization...
» more
Licensing and pricing modelsKubernetes Community Edition: https://hub.helm.sh/charts/splicemachine/splice-helm...
» more
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More resources
ImpalaSphinxSplice Machine
DB-Engines blog posts

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Recent citations in the news

Cloudera Boosts Hadoop App Development On Impala
10 November 2014, InformationWeek

Cloudera’s Impala brings Hadoop to SQL and BI
25 October 2012, ZDNet

Cloudera's a data warehouse player now
28 August 2018, ZDNet

Shark: Real-time queries and analytics for big data
26 November 2012, O'Reilly Radar

Cloudera says Impala is faster than Hive, which isn't saying much
13 January 2014, GigaOM

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16 October 2020, TechRepublic

Splice Machine Announces 3.0 Version of its Intelligent, Distributed SQL Data Platform, Available in Q1 2020
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