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DBMS > Apache Pinot vs. Blazegraph vs. FatDB vs. Google Cloud Datastore

System Properties Comparison Apache Pinot vs. Blazegraph vs. FatDB vs. Google Cloud Datastore

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Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonBlazegraph  Xexclude from comparisonFatDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparison
Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyHigh-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.A .NET NoSQL DBMS that can integrate with and extend SQL Server.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform
Primary database modelRelational DBMSGraph DBMS
RDF store
Document store
Key-value store
Document store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.38
Rank#275  Overall
#126  Relational DBMS
Score0.81
Rank#213  Overall
#19  Graph DBMS
#8  RDF stores
Score4.36
Rank#72  Overall
#12  Document stores
Websitepinot.apache.orgblazegraph.comcloud.google.com/­datastore
Technical documentationdocs.pinot.apache.orgwiki.blazegraph.comcloud.google.com/­datastore/­docs
DeveloperApache Software Foundation and contributorsBlazegraphFatCloudGoogle
Initial release2015200620122008
Current release1.0.0, September 20232.1.5, March 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoextended commercial license availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC#
Server operating systemsAll OS with a Java JDK11 or higherLinux
OS X
Windows
Windowshosted
Data schemeyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyes infoRDF literal typesyesyes, details here
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
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL-like query languageSPARQL is used as query languageno infoVia inetgration in SQL ServerSQL-like query language (GQL)
APIs and other access methodsJDBCJava API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Supported programming languagesGo
Java
Python
.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
C#.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyesyes infovia applicationsusing Google App Engine
Triggersnoyes infovia applicationsCallbacks using the Google Apps Engine
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factorMulti-source replication using Paxos
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.
Foreign keys infoReferential integrityyes infoRelationships in Graphsnoyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoSerializable Isolation within Transactions, Read Committed outside of Transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlSecurity and Authentication via Web Application Container (Tomcat, Jetty)no infoCan implement custom security layer via applicationsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
Apache PinotBlazegraphFatDBGoogle Cloud Datastore
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