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DBMS > AllegroGraph vs. BigObject vs. Databricks vs. Google Cloud Bigtable vs. Tkrzw

System Properties Comparison AllegroGraph vs. BigObject vs. Databricks vs. Google Cloud Bigtable vs. Tkrzw

Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonBigObject  Xexclude from comparisonDatabricks  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSAnalytic DBMS for real-time computations and queriesThe 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.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Relational DBMS infoa hierachical model (tree) can be imposedDocument store
Relational DBMS
Key-value store
Wide column store
Key-value store
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.06
Rank#187  Overall
#30  Document stores
#17  Graph DBMS
#7  RDF stores
#7  Vector DBMS
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.00
Rank#383  Overall
#60  Key-value stores
Websiteallegrograph.combigobject.iowww.databricks.comcloud.google.com/­bigtabledbmx.net/­tkrzw
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmldocs.bigobject.iodocs.databricks.comcloud.google.com/­bigtable/­docs
DeveloperFranz Inc.BigObject, Inc.DatabricksGoogleMikio Hirabayashi
Initial release20042015201320152020
Current release8.0, December 20230.9.3, August 2020
License infoCommercial or Open Sourcecommercial infoLimited community edition freecommercial infofree community edition availablecommercialcommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++
Server operating systemsLinux
OS X
Windows
Linux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
hostedhostedLinux
macOS
Data schemeyes infoRDF schemasyesFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free
Typing infopredefined data types such as float or dateyesyesnono
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 indexesyesyesyesno
SQL infoSupport of SQLSPARQL is used as query languageSQL-like DML and DDL statementswith Databricks SQLnono
APIs and other access methodsRESTful HTTP API
SPARQL
fluentd
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
Python
R
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresyes infoJavaScript or Common LispLuauser defined functions and aggregatesnono
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodeswith FederationnoneShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
noneyesInternal replication in Colossus, and regional replication between two clusters in different zonesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationnoneImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integritynoyes infoautomatically between fact table and dimension tablesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDAtomic single-row operations
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/write lock on objects (tables, trees)yesyesyes
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.noyesnonoyes infousing specific database classes
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no
More information provided by the system vendor
AllegroGraphBigObjectDatabricksGoogle Cloud BigtableTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
Specific characteristicsKnowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more
Supported database models : In addition to the Document store and Relational DBMS...
» more
Competitive advantagesAllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more
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