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DBMS > AllegroGraph vs. Apache IoTDB vs. BigObject vs. Google Cloud Bigtable vs. Tkrzw

System Properties Comparison AllegroGraph vs. Apache IoTDB vs. BigObject vs. Google Cloud Bigtable vs. Tkrzw

Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonApache IoTDB  Xexclude from comparisonBigObject  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 DBMSAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkAnalytic DBMS for real-time computations and queriesGoogle'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
Time Series DBMSRelational DBMS infoa hierachical model (tree) can be imposedKey-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
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.13
Rank#333  Overall
#147  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.comiotdb.apache.orgbigobject.iocloud.google.com/­bigtabledbmx.net/­tkrzw
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmliotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.bigobject.iocloud.google.com/­bigtable/­docs
DeveloperFranz Inc.Apache Software FoundationBigObject, Inc.GoogleMikio Hirabayashi
Initial release20042018201520152020
Current release8.0, December 20231.1.0, April 20230.9.3, August 2020
License infoCommercial or Open Sourcecommercial infoLimited community edition freeOpen Source infoApache Version 2.0commercial infofree community edition availablecommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenononoyesno
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
All OS with a Java VM (>= 1.8)Linux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
hostedLinux
macOS
Data schemeyes infoRDF schemasyesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesnono
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 possiblenononono
Secondary indexesyesyesyesno
SQL infoSupport of SQLSPARQL is used as query languageSQL-like query languageSQL-like DML and DDL statementsnono
APIs and other access methodsRESTful HTTP API
SPARQL
JDBC
Native API
fluentd
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
C
C#
C++
Go
Java
Python
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresyes infoJavaScript or Common LispyesLuanono
Triggersyesyesnonono
Partitioning methods infoMethods for storing different data on different nodeswith Federationhorizontal partitioning (by time range) + vertical partitioning (by deviceId)noneShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasnoneInternal replication in Colossus, and regional replication between two clusters in different zonesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoIntegration with Hadoop and Sparknoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Strong Consistency with Raft
noneImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integritynonoyes infoautomatically between fact table and dimension tablesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoAtomic single-row operations
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoRead/write lock on objects (tables, trees)yesyes
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.noyesyesnoyes infousing specific database classes
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationyesnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no
More information provided by the system vendor
AllegroGraphApache IoTDBBigObjectGoogle Cloud BigtableTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
Specific characteristicsKnowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more
Competitive advantagesAllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more
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