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DBMS > Amazon DocumentDB vs. Datomic vs. Dgraph vs. Google Cloud Datastore vs. HEAVY.AI

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

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonDatomic  Xexclude from comparisonDgraph  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceDatomic 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 hardware
Primary database modelDocument storeRelational DBMSGraph DBMSDocument storeRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
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
Websiteaws.amazon.com/­documentdbwww.datomic.comdgraph.iocloud.google.com/­datastoregithub.com/­heavyai/­heavydb
www.heavy.ai
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.datomic.comdgraph.io/­docscloud.google.com/­datastore/­docsdocs.heavy.ai
DeveloperCognitectDgraph Labs, Inc.GoogleHEAVY.AI, Inc.
Initial release20192012201620082016
Current release1.0.6735, June 20235.10, January 2022
License infoCommercial or Open Sourcecommercialcommercial infolimited edition freeOpen Source infoApache 2.0commercialOpen Source infoApache Version 2; enterprise edition available
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
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 systemshostedAll OS with a Java VMLinux
OS X
Windows
hostedLinux
Data schemeschema-freeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes, 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.nonononono
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLnononoSQL-like query language (GQL)yes
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)RESTful HTTP APIGraphQL query language
gRPC (using protocol buffers) API
HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
Vega
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
Clojure
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
Server-side scripts infoStored proceduresnoyes infoTransaction Functionsnousing Google App Engineno
TriggersnoBy using transaction functionsnoCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesnonenone infoBut extensive use of caching in the application peersyesShardingSharding infoRound robin
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasnone infoBut extensive use of caching in the application peersSynchronous replication via RaftMulti-source replication using PaxosMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nonoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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 Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenonoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno
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
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 developmentnoyes
User concepts infoAccess controlAccess rights for users and rolesnono 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-standard

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