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DBMS > GridDB vs. Hazelcast vs. Postgres-XL vs. Solr

System Properties Comparison GridDB vs. Hazelcast vs. Postgres-XL vs. Solr

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonHazelcast  Xexclude from comparisonPostgres-XL  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionScalable in-memory time series database optimized for IoT and Big DataA widely adopted in-memory data gridBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelTime Series DBMSKey-value storeRelational DBMSSearch engine
Secondary database modelsKey-value store
Relational DBMS
Document store infoJSON support with IMDG 3.12Document store
Spatial DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score0.53
Rank#254  Overall
#117  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Websitegriddb.nethazelcast.comwww.postgres-xl.orgsolr.apache.org
Technical documentationdocs.griddb.nethazelcast.org/­imdg/­docswww.postgres-xl.org/­documentationsolr.apache.org/­resources.html
DeveloperToshiba CorporationHazelcastApache Software Foundation
Initial release201320082014 infosince 2012, originally named StormDB2006
Current release5.1, August 20225.3.6, November 202310 R1, October 20189.6.1, May 2024
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache Version 2; commercial licenses availableOpen Source infoMozilla public licenseOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaCJava
Server operating systemsLinuxAll OS with a Java VMLinux
macOS
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesschema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyesyesyes infosupports customizable data types and automatic typing
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.noyes infothe object must implement a serialization strategyyes infoXML type, but no XML query functionalityyes
Secondary indexesyesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)SQL-like query languageyes infodistributed, parallel query executionSolr Parallel SQL Interface
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JCache
JPA
Memcached protocol
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Java API
RESTful HTTP/JSON API
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnoyes infoEvent Listeners, Executor Servicesuser defined functionsJava plugins
Triggersyesyes infoEventsyesyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infoReplicated Mapyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyesnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelone or two-phase-commit; repeatable reads; read commitedACID infoMVCCoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyes
User concepts infoAccess controlAccess rights for users can be defined per databaseRole-based access controlfine grained access rights according to SQL-standardyes
More information provided by the system vendor
GridDBHazelcastPostgres-XLSolr
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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GridDBHazelcastPostgres-XLSolr
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