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DBMS > Apache Impala vs. Sphinx vs. Warp 10

System Properties Comparison Apache Impala vs. Sphinx vs. Warp 10

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonSphinx  Xexclude from comparisonWarp 10  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopOpen source search engine for searching in data from different sources, e.g. relational databasesTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelRelational DBMSSearch engineTime Series 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
Score6.06
Rank#61  Overall
#6  Search engines
Score0.13
Rank#342  Overall
#32  Time Series DBMS
Websiteimpala.apache.orgsphinxsearch.comwww.warp10.io
Technical documentationimpala.apache.org/­impala-docs.htmlsphinxsearch.com/­docswww.warp10.io/­content/­02_Getting_started
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaSphinx Technologies Inc.SenX
Initial release201320012015
Current release4.1.0, June 20223.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoGPL version 2, commercial licence availableOpen Source infoApache License 2.0
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
Windows
Data schemeyesyesschema-free
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.nono
Secondary indexesyesyes infofull-text index on all search fieldsno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language (SphinxQL)no
APIs and other access methodsJDBC
ODBC
Proprietary protocolHTTP API
Jupyter
WebSocket
Supported programming languagesAll languages supporting JDBC/ODBCC++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyes infoWarpScript
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency infobased on HBase
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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 KerberosnoMandatory use of cryptographic tokens, containing fine-grained authorizations

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Apache ImpalaSphinxWarp 10
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