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DBMS > GRAKN.AI vs. Quasardb vs. TimesTen

System Properties Comparison GRAKN.AI vs. Quasardb vs. TimesTen

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Editorial information provided by DB-Engines
NameGRAKN.AI  Xexclude from comparisonQuasardb  Xexclude from comparisonTimesTen  Xexclude from comparison
DescriptionGrakn is a distributed, hyper-relational database for managing complex data that serves as a knowledge base for cognitive/AI systems.Distributed, high-performance timeseries databaseIn-Memory RDBMS compatible to Oracle
Primary database modelGraph DBMS
Relational DBMS infoOften described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.
Time Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.20
Rank#256  Overall
#21  Graph DBMS
#120  Relational DBMS
Score0.09
Rank#290  Overall
#22  Time Series DBMS
Score2.25
Rank#107  Overall
#52  Relational DBMS
Websitegrakn.aiwww.quasardb.netwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationdev.grakn.ai/­docsdoc.quasardb.netdocs.oracle.com/­database/­timesten-18.1
DeveloperGrakn Labs LtdquasardbOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release201620091998
Current release1.5.8, August 20193.1, January 201911 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourceOpen Source infoGPL Version 3, commercial licenses availablecommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensescommercial
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++
Server operating systemsLinux
OS X
Windows
BSD
Linux
OS X
Windows
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyes infointeger and binaryyes
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.nonono
Secondary indexesyesyes infowith tagsyes
SQL infoSupport of SQLnoSQL-like query languageyes
APIs and other access methodsconsole (shell)
gRPC protocol
Workbase (visualisation software)
HTTP APIJDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languagesAll JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresnonoPL/SQL
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using CassandraSharding infoconsistent hashingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMaster-master replication infoby using CassandraMaster-slave replication with selectable replication factorMaster-master replication
Master-slave replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoby using Apache Kafka and Apache Zookeeperwith Hadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityno infosubstituted by the relationship featurenoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes infoby using LevelDByes 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.noyes infoTransient modeyes
User concepts infoAccess controlyes infoat REST API level; other APIs in progressCryptographically strong user authentication and audit trailfine grained access rights according to SQL-standard
More information provided by the system vendor
GRAKN.AIQuasardbTimesTen
Specific characteristicsGrakn is the knowledge graph to organise complex networks of data and making it queryable,...
» more
High-performance , high-speed, fully integrated timeseries database Seamlessly combines...
» more
The world's first commercial In-Memory Relational Database offering (launched in...
» more
Competitive advantagesExpressive and flexible data model: The meta-schema of Grakn allows for modelling...
» more
High performance in a cost-effective small package Real-time results for even large...
» more
TimesTen offers many advantages over competing products: Mature product with nearly...
» more
Typical application scenariosLife sciences : Grakn makes working with biological data much easier and accelerates...
» more
Tick database Predictive maintenance Pre-deal checks Large scale monitoring
» more
TimesTen can be used in a wide range of application areas. Some examples include:...
» more
Key customersLarge EU investment banks US based hedge funds Orolia Tellmeplus
» more
Some of our key customers include Ericsson , Telcordia , China Mobile, China Telecom,...
» more
Market metricsHas been running in very demanding production environments since 2013 Rapid adoption...
» more
TimesTen is used by thousands of customers in tens of thousands of deployments worldwide...
» more
Licensing and pricing modelsAGPL and Commercial . The commercial license is priced based on cluster resources...
» more
Community edition limited to 2 nodes and 16 GiB of storage per node available for...
» more
Standard Oracle licence models ; end user and ISV/OEM licence terms available.
» more

Related products and services

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More resources
GRAKN.AIQuasardbTimesTen
Conferences and events

Grakn Cosmos, the universal conference of technologies built using Grakn
London, UK, 6-7 February 2020

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