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DBMS > Datomic vs. GridGain vs. Microsoft Azure Synapse Analytics vs. NSDb vs. Typesense

System Properties Comparison Datomic vs. GridGain vs. Microsoft Azure Synapse Analytics vs. NSDb vs. Typesense

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGridGain  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonNSDb  Xexclude from comparisonTypesense  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityGridGain is an in-memory computing platform, built on Apache IgniteElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesA typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivity
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMSTime Series DBMSSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score0.08
Rank#369  Overall
#40  Time Series DBMS
Score0.76
Rank#219  Overall
#14  Search engines
Websitewww.datomic.comwww.gridgain.comazure.microsoft.com/­services/­synapse-analyticsnsdb.iotypesense.org
Technical documentationdocs.datomic.comwww.gridgain.com/­docs/­index.htmldocs.microsoft.com/­azure/­synapse-analyticsnsdb.io/­Architecturetypesense.org/­docs
DeveloperCognitectGridGain Systems, Inc.Microsoft
Initial release20122007201620172015
Current release1.0.7075, December 2023GridGain 8.5.1
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialcommercialOpen Source infoApache Version 2.0Open Source infoGPL V3
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureJava, C++, .NetC++Java, ScalaC++
Server operating systemsAll OS with a Java VMLinux
OS X
Solaris
Windows
hostedLinux
macOS
Linux
Data schemeyesyesyesschema-free infopre-defined schema optional
Typing infopredefined data types such as float or dateyesyesyesyes: int, bigint, decimal, stringyes
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.noyesnono
Secondary indexesyesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLnoANSI-99 for query and DML statements, subset of DDLyesSQL-like query languageno
APIs and other access methodsRESTful HTTP APIHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
ADO.NET
JDBC
ODBC
gRPC
HTTP REST
WebSocket
RESTful HTTP API
Supported programming languagesClojure
Java
C#
C++
Java
PHP
Python
Ruby
Scala
C#
Java
PHP
Java
Scala
.Net infocommunity maintained
Clojure infocommunity maintained
Dart infocommunity maintained
Go infocommunity maintained
Java infocommunity maintained
JavaScript
Perl infocommunity maintained
PHP
Python
Ruby
Rust infocommunity maintained
Swift infocommunity maintained
Server-side scripts infoStored proceduresyes infoTransaction Functionsyes (compute grid and cache interceptors can be used instead)Transact SQLnono
TriggersBy using transaction functionsyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingSharding, horizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersyes (replicated cache)yesMulti-source replication using RAFT
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)nonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDnono
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)yesyesUsing Apache Luceneyes
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 developmentyesyes
User concepts infoAccess controlnoSecurity Hooks for custom implementationsyes

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More resources
DatomicGridGainMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseNSDbTypesense
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