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DBMS > AllegroGraph vs. BigchainDB vs. Databricks vs. Kinetica vs. TimesTen

System Properties Comparison AllegroGraph vs. BigchainDB vs. Databricks vs. Kinetica vs. TimesTen

Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonBigchainDB  Xexclude from comparisonDatabricks  Xexclude from comparisonKinetica  Xexclude from comparisonTimesTen  Xexclude from comparison
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Fully vectorized database across both GPUs and CPUsAn in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Document storeDocument store
Relational DBMS
Relational DBMSRelational DBMS
Secondary database modelsSpatial DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.84
Rank#204  Overall
#35  Document stores
#18  Graph DBMS
#7  RDF stores
#10  Vector DBMS
Score0.76
Rank#216  Overall
#36  Document stores
Score84.24
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score0.42
Rank#261  Overall
#120  Relational DBMS
Score1.26
Rank#164  Overall
#75  Relational DBMS
Websiteallegrograph.comwww.bigchaindb.comwww.databricks.comwww.kinetica.comwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmlbigchaindb.readthedocs.io/­en/­latestdocs.databricks.comdocs.kinetica.comdocs.oracle.com/­en/­database/­other-databases/­timesten/­index.html
DeveloperFranz Inc.DatabricksKineticaOracle infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release20042016201320121998
Current release8.0, December 20237.1, August 2021Release 22.1
License infoCommercial or Open Sourcecommercial infoLimited community edition freeOpen Source infoAGPL v3commercialcommercialcommercial
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 languagePythonC, C++
Server operating systemsLinux
OS X
Windows
LinuxhostedLinuxIBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64
Data schemeyes infoRDF schemasschema-freeFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateyesnoyesyes
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.no infobulk load of XML files possiblenoyesnono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSPARQL is used as query languagenowith Databricks SQLSQL-like DML and DDL statementsyes
APIs and other access methodsRESTful HTTP API
SPARQL
CLI Client
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
Go
Haskell
Java
JavaScript
Python
Ruby
Python
R
Scala
C++
Java
JavaScript (Node.js)
Python
C
C++
Java
Node.js
PL/SQL
Python
Server-side scripts infoStored proceduresyes infoJavaScript or Common Lispuser defined functions and aggregatesuser defined functionsPL/SQL
Triggersyesyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodeswith FederationShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
selectable replication factoryesSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes,with MongoDB ord RethinkDByesyesyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationyesAccess rights for users and roles on table levelfine grained access rights according to SQL-standard
More information provided by the system vendor
AllegroGraphBigchainDBDatabricksKineticaTimesTen
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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