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DBMS > Apache Impala vs. GigaSpaces vs. PouchDB vs. Sphinx

System Properties Comparison Apache Impala vs. GigaSpaces vs. PouchDB vs. Sphinx

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGigaSpaces  Xexclude from comparisonPouchDB  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsJavaScript DBMS with an API inspired by CouchDBOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSDocument store
Object oriented DBMS infoValues are user defined objects
Document storeSearch engine
Secondary database modelsDocument storeGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score15.06
Rank#39  Overall
#24  Relational DBMS
Score1.05
Rank#191  Overall
#31  Document stores
#6  Object oriented DBMS
Score2.70
Rank#114  Overall
#22  Document stores
Score6.06
Rank#61  Overall
#6  Search engines
Websiteimpala.apache.orgwww.gigaspaces.compouchdb.comsphinxsearch.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.gigaspaces.com/­latest/­landing.htmlpouchdb.com/­guidessphinxsearch.com/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGigaspaces TechnologiesApache Software FoundationSphinx Technologies Inc.
Initial release2013200020122001
Current release4.1.0, June 202215.5, September 20207.1.1, June 20193.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2; Commercial licenses availableOpen SourceOpen 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++Java, C++, .NetJavaScriptC++
Server operating systemsLinuxLinux
macOS
Solaris
Windows
server-less, requires a JavaScript environment (browser, Node.js)FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesnono
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 infoXML can be used for describing objects metadatano
Secondary indexesyesyesyes infovia viewsyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-99 for query and DML statementsnoSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
HTTP REST infoonly for PouchDB Server
JavaScript API
Proprietary protocol
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C++
Java
Python
Scala
JavaScriptC++ 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-reduceyesView functions in JavaScriptno
Triggersnoyes, event driven architectureyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infowith a proxy-based framework, named couchdb-loungeSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Multi-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes infoMap-Reduce pattern can be built with XAP task executorsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backendyes 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.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosRole-based access controlnono

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More resources
Apache ImpalaGigaSpacesPouchDBSphinx
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