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DBMS > Datomic vs. Dgraph vs. Google Cloud Datastore vs. HEAVY.AI vs. TimesTen

System Properties Comparison Datomic vs. Dgraph vs. Google Cloud Datastore vs. HEAVY.AI vs. TimesTen

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonDgraph  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonTimesTen  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityDistributed and scalable native Graph DBMSAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareIn-Memory RDBMS compatible to Oracle
Primary database modelRelational DBMSGraph DBMSDocument storeRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score1.53
Rank#152  Overall
#15  Graph DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score1.64
Rank#145  Overall
#67  Relational DBMS
Score1.36
Rank#161  Overall
#75  Relational DBMS
Websitewww.datomic.comdgraph.iocloud.google.com/­datastoregithub.com/­heavyai/­heavydb
www.heavy.ai
www.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationdocs.datomic.comdgraph.io/­docscloud.google.com/­datastore/­docsdocs.heavy.aidocs.oracle.com/­database/­timesten-18.1
DeveloperCognitectDgraph Labs, Inc.GoogleHEAVY.AI, Inc.Oracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release20122016200820161998
Current release1.0.6735, June 20235.10, January 202211 Release 2 (11.2.2.8.0)
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoApache 2.0commercialOpen Source infoApache Version 2; enterprise edition availablecommercial
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureGoC++ and CUDA
Server operating systemsAll OS with a Java VMLinux
OS X
Windows
hostedLinuxAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeyesschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyes, details hereyesyes
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.nonononono
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLnonoSQL-like query language (GQL)yesyes
APIs and other access methodsRESTful HTTP APIGraphQL query language
gRPC (using protocol buffers) API
HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
Vega
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languagesClojure
Java
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All languages supporting JDBC/ODBC/Thrift
Python
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresyes infoTransaction Functionsnousing Google App EnginenoPL/SQL
TriggersBy using transaction functionsnoCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersyesShardingSharding infoRound robinnone
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersSynchronous replication via RaftMulti-source replication using PaxosMulti-source replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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 ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyesyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentnoyesyes
User concepts infoAccess controlnono infoPlanned for future releasesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
DatomicDgraphGoogle Cloud DatastoreHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022TimesTen
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