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DBMS > Apache Impala vs. EJDB vs. GridDB vs. Sphinx

System Properties Comparison Apache Impala vs. EJDB vs. GridDB vs. Sphinx

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonEJDB  Xexclude from comparisonGridDB  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopEmbeddable document-store database library with JSON representation of queries (in MongoDB style)Scalable in-memory time series database optimized for IoT and Big DataOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSDocument storeTime Series DBMSSearch engine
Secondary database modelsDocument storeKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.31
Rank#296  Overall
#44  Document stores
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websiteimpala.apache.orggithub.com/­Softmotions/­ejdbgriddb.netsphinxsearch.com
Technical documentationimpala.apache.org/­impala-docs.htmlgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mddocs.griddb.netsphinxsearch.com/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaSoftmotionsToshiba CorporationSphinx Technologies Inc.
Initial release2013201220132001
Current release4.1.0, June 20225.1, August 20223.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoGPLv2Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++CC++C++
Server operating systemsLinuxserver-lessLinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes infostring, integer, double, bool, date, object_idyes infonumerical, string, blob, geometry, boolean, timestampno
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 indexesyesnoyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL92, SQL-like TQL (Toshiba Query Language)SQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
in-process shared libraryJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Proprietary protocol
Supported programming languagesAll languages supporting JDBC/ODBCActionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++ 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-reducenonono
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integritynono infotypically not needed, however similar functionality with collection joins possiblenono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID at container levelno
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/Write Lockingyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
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 can be defined per databaseno
More information provided by the system vendor
Apache ImpalaEJDBGridDBSphinx
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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Apache ImpalaEJDBGridDBSphinx
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