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DBMS > Datomic vs. FatDB vs. Google Cloud Datastore vs. SAP SQL Anywhere vs. Spark SQL

System Properties Comparison Datomic vs. FatDB vs. Google Cloud Datastore vs. SAP SQL Anywhere vs. Spark SQL

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonFatDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonSAP SQL Anywhere infoformerly called Adaptive Server Anywhere  Xexclude from comparisonSpark SQL  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA .NET NoSQL DBMS that can integrate with and extend SQL Server.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformRDBMS database and synchronization technologies for server, desktop, remote office, and mobile environmentsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSDocument store
Key-value store
Document storeRelational DBMSRelational DBMS
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
Score3.95
Rank#80  Overall
#42  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.datomic.comcloud.google.com/­datastorewww.sap.com/­products/­technology-platform/­sql-anywhere.htmlspark.apache.org/­sql
Technical documentationdocs.datomic.comcloud.google.com/­datastore/­docshelp.sap.com/­docs/­SAP_SQL_Anywherespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperCognitectFatCloudGoogleSAP infoformerly SybaseApache Software Foundation
Initial release20122012200819922014
Current release1.0.7075, December 202317, July 20153.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialcommercialcommercialOpen Source infoApache 2.0
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, ClojureC#Scala
Server operating systemsAll OS with a Java VMWindowshostedAIX
HP-UX
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeyesschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyes, details hereyesyes
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.nonoyesno
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLnono infoVia inetgration in SQL ServerSQL-like query language (GQL)yesSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP API.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
HTTP API
JDBC
ODBC
JDBC
ODBC
Supported programming languagesClojure
Java
C#.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infoTransaction Functionsyes infovia applicationsusing Google App Engineyes, in C/C++, Java, .Net or Perlno
TriggersBy using transaction functionsyes infovia applicationsCallbacks using the Google Apps Engineyesno
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingShardingnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersselectable replication factorMulti-source replication using PaxosSource-replica replication infoDatabase mirroringnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate 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 Consistency
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDno
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 developmentnoyesno
User concepts infoAccess controlnono infoCan implement custom security layer via applicationsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardno

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More resources
DatomicFatDBGoogle Cloud DatastoreSAP SQL Anywhere infoformerly called Adaptive Server AnywhereSpark SQL
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