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DBMS > AllegroGraph vs. Datomic vs. Google Cloud Datastore vs. Splice Machine

System Properties Comparison AllegroGraph vs. Datomic vs. Google Cloud Datastore vs. Splice Machine

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Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonDatomic  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonSplice Machine  Xexclude from comparison
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 durabilityAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Relational DBMSDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.04
Rank#165  Overall
#26  Document stores
#14  Graph DBMS
#7  RDF stores
Score2.94
Rank#101  Overall
#50  Relational DBMS
Score5.51
Rank#67  Overall
#10  Document stores
Score0.91
Rank#179  Overall
#90  Relational DBMS
Websiteallegrograph.comwww.datomic.comcloud.google.com/­datastoresplicemachine.com
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmldocs.datomic.comcloud.google.com/­datastore/­docsdoc.splicemachine.com
DeveloperFranz Inc.CognitectGoogleSplice Machine
Initial release2004201220082014
Current release7.0.0, April 20200.9.5951, July 20192.0
License infoCommercial or Open Sourcecommercial infoLimited community edition freecommercial infolimited edition freecommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureJava
Server operating systemsLinux
OS X
Windows
All OS with a Java VMhostedLinux
OS X
Solaris
Windows
Data schemeyes infoRDF schemasyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes, details hereyes
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 possiblenono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSPARQL is used as query languagenoSQL-like query language (GQL)yes
APIs and other access methodsRESTful HTTP API
SPARQL
RESTful HTTP APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
Clojure
Java
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infoJavaScript or Common Lispyes infoTransaction Functionsusing Google App Engineyes infoJava
TriggersyesBy using transaction functionsCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodeswith Federationnone infoBut extensive use of caching in the application peersShardingShared Nothhing Auto-Sharding, Columnar Partitioning
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 using PaxosMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud DataflowYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate 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.Immediate Consistency
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
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 authenticationnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
AllegroGraphDatomicGoogle Cloud DatastoreSplice Machine
Specific characteristicsKnowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more
THE ONLY SCALE-OUT SQL RDBMS WITH BUILT-IN MACHINE LEARNING For data-rich, real-time...
» more
Competitive advantagesAllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more
Operational Workloads: Full ACID support with high performance at scale Multi-row...
» more
Typical application scenariosNew AI/ML and IoT Applications Data Warehouse Offloads Application Modernization...
» more
Licensing and pricing modelsKubernetes Community Edition: https://hub.helm.sh/charts/splicemachine/splice-helm...
» more
News

Data Fabrics and Knowledge Graphs — A Symbiotic Relationship
6 November 2020

RDF vs Property Graph – The Graph Show
3 November 2020

Text Analytics Forum 2020 – KMWorld Connect
27 October 2020

Sharing Ontologies Globally To Speed Science And Healthcare Solutions – OntoPortal
7 October 2020

Knowledge Graphs: A Single Source of Truth for the Enterprise
5 October 2020

How To Get Real-Time Analytics By Consolidating Databases
21 May 2020

How to Cut Costs and Digitally Transform
1 May 2020

How To Migrate A Legacy SQL Application To The Cloud With AI
10 March 2020

Building Production-Ready Machine Learning Models
4 March 2020

Considerations of Moving Applications Off the Mainframe
22 January 2020

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
AllegroGraphDatomicGoogle Cloud DatastoreSplice Machine
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