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DBMS > CrateDB vs. GridDB vs. Microsoft Azure Synapse Analytics vs. Valentina Server

System Properties Comparison CrateDB vs. GridDB vs. Microsoft Azure Synapse Analytics vs. Valentina Server

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonGridDB  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonValentina Server  Xexclude from comparison
DescriptionDistributed Database based on LuceneScalable in-memory time series database optimized for IoT and Big DataElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerObject-relational database and reports server
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Time Series DBMSRelational DBMSRelational DBMS
Secondary database modelsRelational DBMSKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.71
Rank#227  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#10  Vector DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score0.21
Rank#325  Overall
#144  Relational DBMS
Websitecratedb.comgriddb.netazure.microsoft.com/­services/­synapse-analyticswww.valentina-db.net
Technical documentationcratedb.com/­docsdocs.griddb.netdocs.microsoft.com/­azure/­synapse-analyticsvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperCrateToshiba CorporationMicrosoftParadigma Software
Initial release2013201320161999
Current release5.1, August 20225.7.5
License infoCommercial or Open SourceOpen SourceOpen 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 servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C++
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinuxhostedLinux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesyes
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyesyes
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.nonono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilitySQL92, SQL-like TQL (Toshiba Query Language)yesyes
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
ODBC
Supported programming languages.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
Java
PHP
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresuser defined functions (Javascript)noTransact SQLyes
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding, horizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelSource-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Immediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integritynonono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infounique row identifiers can be used for implementing an optimistic concurrency control strategyACID at container levelACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.noyesyes
User concepts infoAccess controlrights management via user accountsAccess rights for users can be defined per databaseyesfine grained access rights according to SQL-standard
More information provided by the system vendor
CrateDBGridDBMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseValentina Server
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
CrateDBGridDBMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseValentina Server
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