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DBMS > AllegroGraph vs. Datomic vs. Drizzle vs. Google Cloud Bigtable vs. Oracle Coherence

System Properties Comparison AllegroGraph vs. Datomic vs. Drizzle vs. Google Cloud Bigtable vs. Oracle Coherence

Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonDatomic  Xexclude from comparisonDrizzle  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonOracle Coherence  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Oracles in-memory data grid solution
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Relational DBMSRelational DBMSKey-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
Score0.84
Rank#204  Overall
#35  Document stores
#18  Graph DBMS
#7  RDF stores
#10  Vector DBMS
Score1.55
Rank#144  Overall
#67  Relational DBMS
Score2.97
Rank#92  Overall
#15  Key-value stores
#8  Wide column stores
Score1.90
Rank#127  Overall
#21  Key-value stores
Websiteallegrograph.comwww.datomic.comcloud.google.com/­bigtablewww.oracle.com/­java/­coherence
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmldocs.datomic.comcloud.google.com/­bigtable/­docsdocs.oracle.com/­en/­middleware/­standalone/­coherence
DeveloperFranz Inc.CognitectDrizzle project, originally started by Brian AkerGoogleOracle
Initial release20042012200820152007
Current release8.0, December 20231.0.7180, July 20247.2.4, September 201214.1, August 2023
License infoCommercial or Open Sourcecommercial infoLimited community edition freecommercial infolimited edition freeOpen Source infoGNU GPLcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureC++Java
Server operating systemsLinux
OS X
Windows
All OS with a Java VMFreeBSD
Linux
OS X
hostedAll OS with a Java VM
Data schemeyes infoRDF schemasyesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesnoyes
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 possiblenonono
Secondary indexesyesyesyesnono
SQL infoSupport of SQLSPARQL is used as query languagenoyes infowith proprietary extensionsnono
APIs and other access methodsRESTful HTTP API
SPARQL
RESTful HTTP APIJDBCgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JCache
JPA
RESTful HTTP API
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
Clojure
Java
C
C++
Java
PHP
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C++
Java
Server-side scripts infoStored proceduresyes infoJavaScript or Common Lispyes infoTransaction Functionsnonono
TriggersyesBy using transaction functionsno infohooks for callbacks inside the server can be used.noyes infoLive Events
Partitioning methods infoMethods for storing different data on different nodeswith Federationnone infoBut extensive use of caching in the application peersShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
none infoBut extensive use of caching in the application peersMulti-source replication
Source-replica replication
Internal replication in Colossus, and regional replication between two clusters in different zonesyes, with selectable consistency level
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDAtomic single-row operationsconfigurable
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes infooptionally
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes inforecommended only for testing and developmentnoyes
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationnoPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)authentification to access the cache via certificates or http basic authentication
More information provided by the system vendor
AllegroGraphDatomicDrizzleGoogle Cloud BigtableOracle Coherence
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More resources
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