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DBMS > Blazegraph vs. EsgynDB vs. EXASOL vs. Firebase Realtime Database vs. Google Cloud Bigtable

System Properties Comparison Blazegraph vs. EsgynDB vs. EXASOL vs. Firebase Realtime Database vs. Google Cloud Bigtable

Editorial information provided by DB-Engines
NameBlazegraph  Xexclude from comparisonEsgynDB  Xexclude from comparisonEXASOL  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGoogle Cloud Bigtable  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.Enterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.
Primary database modelGraph DBMS
RDF store
Relational DBMSRelational DBMSDocument storeKey-value store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.81
Rank#213  Overall
#19  Graph DBMS
#8  RDF stores
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score1.76
Rank#139  Overall
#62  Relational DBMS
Score13.64
Rank#39  Overall
#6  Document stores
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Websiteblazegraph.comwww.esgyn.cnwww.exasol.comfirebase.google.com/­products/­realtime-databasecloud.google.com/­bigtable
Technical documentationwiki.blazegraph.comwww.exasol.com/­resourcesfirebase.google.com/­docs/­databasecloud.google.com/­bigtable/­docs
DeveloperBlazegraphEsgynExasolGoogle infoacquired by Google 2014Google
Initial release20062015200020122015
Current release2.1.5, March 2019
License infoCommercial or Open SourceOpen Source infoextended commercial license availablecommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, Java
Server operating systemsLinux
OS X
Windows
Linuxhostedhosted
Data schemeschema-freeyesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyes infoRDF literal typesyesyesyesno
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.nononono
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLSPARQL is used as query languageyesyesnono
APIs and other access methodsJava API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
ADO.NET
JDBC
ODBC
.Net
JDBC
ODBC
WebSocket
Android
iOS
JavaScript API
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Supported programming languages.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
All languages supporting JDBC/ODBC/ADO.NetJava
Lua
Python
R
Java
JavaScript
Objective-C
C#
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesJava Stored Proceduresuser defined functionslimited functionality with using 'rules'no
TriggersnonoyesCallbacks are triggered when data changesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infoHadoop integrationnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integrityyes infoRelationships in Graphsyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDyesAtomic single-row operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.noyesno
User concepts infoAccess controlSecurity and Authentication via Web Application Container (Tomcat, Jetty)fine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standardyes, based on authentication and database rulesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
BlazegraphEsgynDBEXASOLFirebase Realtime DatabaseGoogle Cloud Bigtable
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