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DBMS > Apache Solr vs. GridDB vs. Microsoft Azure Cosmos DB vs. SvectorDB

System Properties Comparison Apache Solr vs. GridDB vs. Microsoft Azure Cosmos DB vs. SvectorDB

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Editorial information provided by DB-Engines
NameApache Solr  Xexclude from comparisonGridDB  Xexclude from comparisonMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB  Xexclude from comparisonSvectorDB  Xexclude from comparison
DescriptionA widely used distributed, scalable search engine based on Apache LuceneScalable in-memory time series database optimized for IoT and Big DataGlobally distributed, horizontally scalable, multi-model database serviceServerless cloud-native vector database infoServerless cloud-native vector database
Primary database modelSearch engineTime Series DBMSDocument store
Graph DBMS
Key-value store
Wide column store
Vector DBMS
Secondary database modelsSpatial DBMSKey-value store
Relational DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score32.79
Rank#23  Overall
#3  Search engines
Score2.00
Rank#114  Overall
#9  Time Series DBMS
Score22.94
Rank#26  Overall
#4  Document stores
#2  Graph DBMS
#3  Key-value stores
#2  Wide column stores
Score0.00
Rank#385  Overall
#21  Vector DBMS
Websitesolr.apache.orggriddb.netazure.microsoft.com/­services/­cosmos-dbsvectordb.com
Technical documentationsolr.apache.org/­resources.htmldocs.griddb.netlearn.microsoft.com/­azure/­cosmos-dbwww.svectordb.com/­docs
DeveloperApache Software FoundationToshiba CorporationMicrosoftSvectorDB
Initial release2006201320142023
Current release9.6.1, May 20245.1, August 2022
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 availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++
Server operating systemsAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linuxhostedserver-less
Data schemeyes infoDynamic Fields enables on-the-fly addition of new fieldsyesschema-free
Typing infopredefined data types such as float or dateyes infosupports customizable data types and automatic typingyes infonumerical, string, blob, geometry, boolean, timestampyes infoJSON typesstring, double, vector
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.yesnono
Secondary indexesyes infoAll search fields are automatically indexedyesyes infoAll properties auto-indexed by default
SQL infoSupport of SQLSolr Parallel SQL InterfaceSQL92, SQL-like TQL (Toshiba Query Language)SQL-like query language
APIs and other access methodsJava API
RESTful HTTP/JSON API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API
OpenAPI 3.0, RESTful HTTP API, Python SDK, JavaScript / TypeScript SDK
Supported programming languages.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python
Server-side scripts infoStored proceduresJava pluginsnoJavaScript
Triggersyes infoUser configurable commands triggered on index changesyesJavaScript
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationyes infoImplicit feature of the cloud service
MapReduce infoOffers an API for user-defined Map/Reduce methodsspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobswith Hadoop integration infoIntegration with Hadoop/HDInsight on Azure*
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency within container, eventual consistency across containersBounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency infoConsistency level configurable on request level
Session Consistency
Immediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataoptimistic lockingACID at container levelMulti-item ACID transactions with snapshot isolation within a partition
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.yesyes
User concepts infoAccess controlyesAccess rights for users can be defined per databaseAccess rights can be defined down to the item level
More information provided by the system vendor
Apache SolrGridDBMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBSvectorDB
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
Apache SolrGridDBMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBSvectorDB
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