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DBMS > Datomic vs. Dgraph vs. EsgynDB vs. Google Cloud Bigtable vs. HarperDB

System Properties Comparison Datomic vs. Dgraph vs. EsgynDB vs. Google Cloud Bigtable vs. HarperDB

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonDgraph  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHarperDB  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityDistributed and scalable native Graph DBMSEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.
Primary database modelRelational DBMSGraph DBMSRelational DBMSKey-value store
Wide column store
Document store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score1.45
Rank#156  Overall
#15  Graph DBMS
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.55
Rank#248  Overall
#38  Document stores
Websitewww.datomic.comdgraph.iowww.esgyn.cncloud.google.com/­bigtablewww.harperdb.io
Technical documentationdocs.datomic.comdgraph.io/­docscloud.google.com/­bigtable/­docsdocs.harperdb.io/­docs
DeveloperCognitectDgraph Labs, Inc.EsgynGoogleHarperDB
Initial release20122016201520152017
Current release1.0.6735, June 20233.1, August 2021
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoApache 2.0commercialcommercialcommercial infofree community edition available
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 languageJava, ClojureGoC++, JavaNode.js
Server operating systemsAll OS with a Java VMLinux
OS X
Windows
LinuxhostedLinux
OS X
Data schemeyesschema-freeyesschema-freedynamic schema
Typing infopredefined data types such as float or dateyesyesyesnoyes infoJSON data types
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 SQLnonoyesnoSQL-like data manipulation statements
APIs and other access methodsRESTful HTTP APIGraphQL query language
gRPC (using protocol buffers) API
HTTP API
ADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
Supported programming languagesClojure
Java
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
Server-side scripts infoStored proceduresyes infoTransaction FunctionsnoJava Stored ProceduresnoCustom Functions infosince release 3.1
TriggersBy using transaction functionsnononono
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersyesShardingShardingA table resides as a whole on one (or more) nodes in a cluster
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersSynchronous replication via RaftMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zonesyes infothe nodes on which a table resides can be defined
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDAtomic single-row operationsAtomic execution of specific operations
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, using LMDB
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 developmentnonoyes
User concepts infoAccess controlnono infoPlanned for future releasesfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles

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More resources
DatomicDgraphEsgynDBGoogle Cloud BigtableHarperDB
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