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DBMS > Datomic vs. Google Cloud Datastore vs. Microsoft Azure Synapse Analytics vs. NSDb vs. PouchDB

System Properties Comparison Datomic vs. Google Cloud Datastore vs. Microsoft Azure Synapse Analytics vs. NSDb vs. PouchDB

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonNSDb  Xexclude from comparisonPouchDB  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformElastic, 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 KubernetesJavaScript DBMS with an API inspired by CouchDB
Primary database modelRelational DBMSDocument storeRelational DBMSTime Series DBMSDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score0.08
Rank#369  Overall
#40  Time Series DBMS
Score2.34
Rank#112  Overall
#21  Document stores
Websitewww.datomic.comcloud.google.com/­datastoreazure.microsoft.com/­services/­synapse-analyticsnsdb.iopouchdb.com
Technical documentationdocs.datomic.comcloud.google.com/­datastore/­docsdocs.microsoft.com/­azure/­synapse-analyticsnsdb.io/­Architecturepouchdb.com/­guides
DeveloperCognitectGoogleMicrosoftApache Software Foundation
Initial release20122008201620172012
Current release1.0.7075, December 20237.1.1, June 2019
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialcommercialOpen Source infoApache Version 2.0Open Source
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureC++Java, ScalaJavaScript
Server operating systemsAll OS with a Java VMhostedhostedLinux
macOS
server-less, requires a JavaScript environment (browser, Node.js)
Data schemeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyes, details hereyesyes: int, bigint, decimal, stringno
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.nonononono
Secondary indexesyesyesyesall fields are automatically indexedyes infovia views
SQL infoSupport of SQLnoSQL-like query language (GQL)yesSQL-like query languageno
APIs and other access methodsRESTful HTTP APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
gRPC
HTTP REST
WebSocket
HTTP REST infoonly for PouchDB Server
JavaScript API
Supported programming languagesClojure
Java
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
Java
PHP
Java
Scala
JavaScript
Server-side scripts infoStored proceduresyes infoTransaction Functionsusing Google App EngineTransact SQLnoView functions in JavaScript
TriggersBy using transaction functionsCallbacks using the Google Apps Enginenoyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingSharding, horizontal partitioningShardingSharding infowith a proxy-based framework, named couchdb-lounge
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replication using PaxosyesMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate ConsistencyEventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsno 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 dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesUsing Apache Luceneyes infoby using IndexedDB, WebSQL or LevelDB as backend
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 developmentnoyes
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yesno

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More resources
DatomicGoogle Cloud DatastoreMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseNSDbPouchDB
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