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

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

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonFatDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonjBASE  Xexclude from comparisonSAP SQL Anywhere infoformerly called Adaptive Server Anywhere  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 PlatformA robust multi-value DBMS comprising development tools and middlewareRDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments
Primary database modelRelational DBMSDocument store
Key-value store
Document storeMultivalue 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
Score1.49
Rank#156  Overall
#3  Multivalue DBMS
Score3.95
Rank#80  Overall
#42  Relational DBMS
Websitewww.datomic.comcloud.google.com/­datastorewww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-jbasewww.sap.com/­products/­technology-platform/­sql-anywhere.html
Technical documentationdocs.datomic.comcloud.google.com/­datastore/­docsdocs.rocketsoftware.com/­bundle?labelkey=jbase_5.9help.sap.com/­docs/­SAP_SQL_Anywhere
DeveloperCognitectFatCloudGoogleRocket Software (formerly Zumasys)SAP infoformerly Sybase
Initial release20122012200819911992
Current release1.0.6735, June 20235.717, July 2015
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialcommercialcommercialcommercial
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#
Server operating systemsAll OS with a Java VMWindowshostedAIX
Linux
Windows
AIX
HP-UX
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes, details hereoptionalyes
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.nonoyesyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLnono infoVia inetgration in SQL ServerSQL-like query language (GQL)Embedded SQL for jBASE in BASICyes
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
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API
ADO.NET
HTTP API
JDBC
ODBC
Supported programming languagesClojure
Java
C#.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Basic
Jabbascript
Java
C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infoTransaction Functionsyes infovia applicationsusing Google App Engineyesyes, in C/C++, Java, .Net or Perl
TriggersBy using transaction functionsyes infovia applicationsCallbacks using the Google Apps Engineyesyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersselectable replication factorMulti-source replication using PaxosyesSource-replica replication infoDatabase mirroring
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infousing Google Cloud Dataflownono
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 pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID
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 developmentnoyesyes
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)Access rights can be defined down to the item levelfine grained access rights according to SQL-standard

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More resources
DatomicFatDBGoogle Cloud DatastorejBASESAP SQL Anywhere infoformerly called Adaptive Server Anywhere
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