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DBMS > Datomic vs. Elasticsearch vs. GridDB vs. Hive vs. Microsoft Azure Synapse Analytics

System Properties Comparison Datomic vs. Elasticsearch vs. GridDB vs. Hive vs. Microsoft Azure Synapse Analytics

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonElasticsearch  Xexclude from comparisonGridDB  Xexclude from comparisonHive  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricScalable in-memory time series database optimized for IoT and Big Datadata warehouse software for querying and managing large distributed datasets, built on HadoopElastic, large scale data warehouse service leveraging the broad eco-system of SQL Server
Primary database modelRelational DBMSSearch engineTime Series DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
Key-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score132.83
Rank#7  Overall
#1  Search engines
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score19.93
Rank#31  Overall
#19  Relational DBMS
Websitewww.datomic.comwww.elastic.co/­elasticsearchgriddb.nethive.apache.orgazure.microsoft.com/­services/­synapse-analytics
Technical documentationdocs.datomic.comwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmldocs.griddb.netcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.microsoft.com/­azure/­synapse-analytics
DeveloperCognitectElasticToshiba CorporationApache Software Foundation infoinitially developed by FacebookMicrosoft
Initial release20122010201320122016
Current release1.0.7075, December 20238.6, January 20235.1, August 20223.1.3, April 2022
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoElastic LicenseOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureJavaC++JavaC++
Server operating systemsAll OS with a Java VMAll OS with a Java VMLinuxAll OS with a Java VMhosted
Data schemeyesschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesyesyes
Typing infopredefined data types such as float or dateyesyesyes 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.nononono
Secondary indexesyesyes infoAll search fields are automatically indexedyesyesyes
SQL infoSupport of SQLnoSQL-like query languageSQL92, SQL-like TQL (Toshiba Query Language)SQL-like DML and DDL statementsyes
APIs and other access methodsRESTful HTTP APIJava API
RESTful HTTP/JSON API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
ADO.NET
JDBC
ODBC
Supported programming languagesClojure
Java
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++
Java
PHP
Python
C#
Java
PHP
Server-side scripts infoStored proceduresyes infoTransaction Functionsyesnoyes infouser defined functions and integration of map-reduceTransact SQL
TriggersBy using transaction functionsyes infoby using the 'percolation' featureyesnono
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingShardingShardingSharding, horizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersyesSource-replica replicationselectable replication factoryes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoES-Hadoop ConnectorConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allImmediate consistency within container, eventual consistency across containersEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraints
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID at container levelnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentMemcached and Redis integrationyes
User concepts infoAccess controlnoAccess rights for users can be defined per databaseAccess rights for users, groups and rolesyes
More information provided by the system vendor
DatomicElasticsearchGridDBHiveMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse
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
DatomicElasticsearchGridDBHiveMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse
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