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DBMS > FatDB vs. Microsoft Azure SQL Database vs. Splice Machine vs. Stardog vs. Vertica

System Properties Comparison FatDB vs. Microsoft Azure SQL Database vs. Splice Machine vs. Stardog vs. Vertica

Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonSplice Machine  Xexclude from comparisonStardog  Xexclude from comparisonVertica infoOpenText™ Vertica™  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.Database as a Service offering with high compatibility to Microsoft SQL ServerOpen-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 virtualizationCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelDocument store
Key-value store
Relational DBMSRelational DBMSGraph DBMS
RDF store
Relational DBMS infoColumn oriented
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websiteazure.microsoft.com/­en-us/­products/­azure-sql/­databasesplicemachine.comwww.stardog.comwww.vertica.com
Technical documentationdocs.microsoft.com/­en-us/­azure/­azure-sqlsplicemachine.com/­how-it-worksdocs.stardog.comvertica.com/­documentation
DeveloperFatCloudMicrosoftSplice MachineStardog-UnionOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20122010201420102005
Current releaseV123.1, March 20217.3.0, May 202012.0.3, January 2023
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/studentscommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenoyesnonono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#C++JavaJavaC++
Server operating systemsWindowshostedLinux
OS X
Solaris
Windows
Linux
macOS
Windows
Linux
Data schemeschema-freeyesyesschema-free and OWL/RDFS-schema supportYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.yesno infoImport/export of XML data possibleno
Secondary indexesyesyesyesyes infosupports real-time indexing in full-text and geospatialNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLno infoVia inetgration in SQL ServeryesyesYes, compatible with all major SQL variants through dedicated BI/SQL ServerFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
ADO.NET
JDBC
ODBC
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
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC#.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyes infovia applicationsTransact SQLyes infoJavauser defined functions and aggregates, HTTP Server extensions in Javayes, PostgreSQL PL/pgSQL, with minor differences
Triggersyes infovia applicationsyesyesyes infovia event handlersyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingShared Nothhing Auto-Sharding, Columnar Partitioningnonehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes, with always 3 replicas availableMulti-source replication
Source-replica replication
Multi-source replication in HA-ClusterMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoYes, via Full Spark Integrationnono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate ConsistencyImmediate Consistency in HA-ClusterImmediate Consistency
Foreign keys infoReferential integritynoyesyesyes inforelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlno infoCan implement custom security layer via applicationsfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standardAccess rights for users and rolesfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
FatDBMicrosoft Azure SQL Database infoformerly SQL AzureSplice MachineStardogVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
» more

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More resources
FatDBMicrosoft Azure SQL Database infoformerly SQL AzureSplice MachineStardogVertica infoOpenText™ Vertica™
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