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DBMS > Blazegraph vs. InfinityDB vs. Kinetica vs. Tigris

System Properties Comparison Blazegraph vs. InfinityDB vs. Kinetica vs. Tigris

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Editorial information provided by DB-Engines
NameBlazegraph  Xexclude from comparisonInfinityDB  Xexclude from comparisonKinetica  Xexclude from comparisonTigris  Xexclude from comparison
Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.
DescriptionHigh-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.A Java embedded Key-Value Store which extends the Java Map interfaceFully vectorized database across both GPUs and CPUsA horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructure
Primary database modelGraph DBMS
RDF store
Key-value storeRelational DBMSDocument store
Key-value store
Search engine
Time Series DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.74
Rank#217  Overall
#19  Graph DBMS
#8  RDF stores
Score0.00
Rank#383  Overall
#59  Key-value stores
Score0.42
Rank#261  Overall
#120  Relational DBMS
Score0.05
Rank#359  Overall
#50  Document stores
#52  Key-value stores
#23  Search engines
#37  Time Series DBMS
Websiteblazegraph.comboilerbay.comwww.kinetica.comwww.tigrisdata.com
Technical documentationwiki.blazegraph.comboilerbay.com/­infinitydb/­manualdocs.kinetica.comwww.tigrisdata.com/­docs
DeveloperBlazegraphBoiler Bay Inc.KineticaTigris Data, Inc.
Initial release2006200220122022
Current release2.1.5, March 20194.07.1, August 2021
License infoCommercial or Open SourceOpen Source infoextended commercial license availablecommercialcommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC, C++
Server operating systemsLinux
OS X
Windows
All OS with a Java VMLinuxLinux
macOS
Windows
Data schemeschema-freeyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeyesyes
Typing infopredefined data types such as float or dateyes infoRDF literal typesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyesyes
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 indexesyesno infomanual creation possible, using inversions based on multi-value capabilityyesyes
SQL infoSupport of SQLSPARQL is used as query languagenoSQL-like DML and DDL statementsno
APIs and other access methodsJava API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
JDBC
ODBC
RESTful HTTP API
CLI Client
gRPC
RESTful HTTP API
Supported programming languages.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
JavaC++
Java
JavaScript (Node.js)
Python
Go
Java
JavaScript (Node.js)
Server-side scripts infoStored proceduresyesnouser defined functionsno
Triggersnonoyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneSource-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency infoREAD-COMMITTED or SERIALIZEDImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in Graphsno infomanual creation possible, using inversions based on multi-value capabilityyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoOptimistic locking for transactions; no isolation for bulk loadsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes, using FoundationDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoGPU vRAM or System RAM
User concepts infoAccess controlSecurity and Authentication via Web Application Container (Tomcat, Jetty)noAccess rights for users and roles on table levelAccess rights for users and roles

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More resources
BlazegraphInfinityDBKineticaTigris
Recent citations in the news

Video: Blazegraph Accelerates Graph Computing with GPUs
20 December 2015, insideHPC

Harnessing GPUs Delivers a Big Speedup for Graph Analytics
15 December 2015, Datanami

This AI Paper Introduces A Comprehensive RDF Dataset With Over 26 Billion Triples Covering Scholarly Data Across All Scientific Disciplines
19 August 2023, MarkTechPost

provided by Google News

Kinetica Elevates RAG with Fast Access to Real-Time Data
26 March 2024, Datanami

Kinetica Delivers Real-Time Vector Similarity Search
21 March 2024, insideBIGDATA

Kinetica ramps up RAG for generative AI, empowering enterprises with real-time operational data
18 March 2024, SiliconANGLE News

Kinetica: AI is a ‘killer app’ for data analytics
2 May 2023, Blocks & Files

Kinetica Taps Dell for Hardware
12 June 2018, Finovate

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Tigris Data Unveils Beta Launch of New Vector Search Tool
19 May 2023, Datanami

Tigris Data Launches All-in-One Developer Data Platform
27 September 2022, Datanami

provided by Google News



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