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DBMS > Drizzle vs. GridDB vs. Solr vs. Splice Machine

System Properties Comparison Drizzle vs. GridDB vs. Solr vs. Splice Machine

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonGridDB  Xexclude from comparisonSolr  Xexclude from comparisonSplice Machine  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Scalable in-memory time series database optimized for IoT and Big DataA widely used distributed, scalable search engine based on Apache LuceneOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSTime Series DBMSSearch engineRelational DBMS
Secondary database modelsKey-value store
Relational DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitegriddb.netsolr.apache.orgsplicemachine.com
Technical documentationdocs.griddb.netsolr.apache.org/­resources.htmlsplicemachine.com/­how-it-works
DeveloperDrizzle project, originally started by Brian AkerToshiba CorporationApache Software FoundationSplice Machine
Initial release2008201320062014
Current release7.2.4, September 20125.1, August 20229.6.0, April 20243.1, March 2021
License infoCommercial or Open SourceOpen Source infoGNU GPLOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache Version 2Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++JavaJava
Server operating systemsFreeBSD
Linux
OS X
LinuxAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Solaris
Windows
Data schemeyesyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyes infosupports customizable data types and automatic typingyes
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
Secondary indexesyesyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLyes infowith proprietary extensionsSQL92, SQL-like TQL (Toshiba Query Language)Solr Parallel SQL Interfaceyes
APIs and other access methodsJDBCJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Java API
RESTful HTTP/JSON API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C++
Java
PHP
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnonoJava pluginsyes infoJava
Triggersno infohooks for callbacks inside the server can be used.yesyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replicationyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container leveloptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
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.yesyesyes
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users can be defined per databaseyesAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
DrizzleGridDBSolrSplice Machine
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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More resources
DrizzleGridDBSolrSplice Machine
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