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DBMS > FatDB vs. Google Cloud Spanner vs. Splice Machine vs. Stardog

System Properties Comparison FatDB vs. Google Cloud Spanner vs. Splice Machine vs. Stardog

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonSplice Machine  Xexclude from comparisonStardog  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionA .NET NoSQL DBMS that can integrate with and extend SQL Server.A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelDocument store
Key-value store
Relational DBMSRelational DBMSGraph DBMS
RDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Websitecloud.google.com/­spannersplicemachine.comwww.stardog.com
Technical documentationcloud.google.com/­spanner/­docssplicemachine.com/­how-it-worksdocs.stardog.com
DeveloperFatCloudGoogleSplice MachineStardog-Union
Initial release2012201720142010
Current release3.1, March 20217.3.0, May 2020
License infoCommercial or Open SourcecommercialcommercialOpen Source infoAGPL 3.0, commercial license availablecommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#JavaJava
Server operating systemsWindowshostedLinux
OS X
Solaris
Windows
Linux
macOS
Windows
Data schemeschema-freeyesyesschema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or dateyesyesyesyes
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.nono infoImport/export of XML data possible
Secondary indexesyesyesyesyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLno infoVia inetgration in SQL Serveryes infoQuery statements complying to ANSI 2011yesYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
Supported programming languagesC#Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresyes infovia applicationsnoyes infoJavauser defined functions and aggregates, HTTP Server extensions in Java
Triggersyes infovia applicationsnoyesyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShared Nothhing Auto-Sharding, Columnar Partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication with 3 replicas for regional instances.Multi-source replication
Source-replica replication
Multi-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infousing Google Cloud DataflowYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate ConsistencyImmediate Consistency in HA-Cluster
Foreign keys infoReferential integritynoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityyesyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoStrict serializable isolationACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlno infoCan implement custom security layer via applicationsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles according to SQL-standardAccess rights for users and roles

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More resources
FatDBGoogle Cloud SpannerSplice MachineStardog
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