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DBMS > Apache Impala vs. GridDB vs. PouchDB vs. Solr vs. TimescaleDB

System Properties Comparison Apache Impala vs. GridDB vs. PouchDB vs. Solr vs. TimescaleDB

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGridDB  Xexclude from comparisonPouchDB  Xexclude from comparisonSolr  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopScalable in-memory time series database optimized for IoT and Big DataJavaScript DBMS with an API inspired by CouchDBA widely used distributed, scalable search engine based on Apache LuceneA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSTime Series DBMSDocument storeSearch engineTime Series DBMS
Secondary database modelsDocument storeKey-value store
Relational DBMS
Spatial DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score2.28
Rank#115  Overall
#21  Document stores
Score42.91
Rank#24  Overall
#3  Search engines
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websiteimpala.apache.orggriddb.netpouchdb.comsolr.apache.orgwww.timescale.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.griddb.netpouchdb.com/­guidessolr.apache.org/­resources.htmldocs.timescale.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaToshiba CorporationApache Software FoundationApache Software FoundationTimescale
Initial release20132013201220062017
Current release4.1.0, June 20225.1, August 20227.1.1, June 20199.6.0, April 20242.13.0, November 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen SourceOpen Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++JavaScriptJavaC
Server operating systemsLinuxLinuxserver-less, requires a JavaScript environment (browser, Node.js)All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Data schemeyesyesschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampnoyes infosupports customizable data types and automatic typingnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.nononoyesyes
Secondary indexesyesyesyes infovia viewsyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL92, SQL-like TQL (Toshiba Query Language)noSolr Parallel SQL Interfaceyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HTTP REST infoonly for PouchDB Server
JavaScript API
Java API
RESTful HTTP/JSON API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesAll languages supporting JDBC/ODBCC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
JavaScript.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoView functions in JavaScriptJava pluginsuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnoyesyesyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infowith a proxy-based framework, named couchdb-loungeShardingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
yesSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency within container, eventual consistency across containersEventual ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID at container levelnooptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backendyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users can be defined per databasenoyesfine grained access rights according to SQL-standard
More information provided by the system vendor
Apache ImpalaGridDBPouchDBSolrTimescaleDB
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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Apache ImpalaGridDBPouchDBSolrTimescaleDB
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