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DBMS > Dgraph vs. EsgynDB vs. Google Cloud Datastore vs. HarperDB vs. OrigoDB

System Properties Comparison Dgraph vs. EsgynDB vs. Google Cloud Datastore vs. HarperDB vs. OrigoDB

Editorial information provided by DB-Engines
NameDgraph  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHarperDB  Xexclude from comparisonOrigoDB  Xexclude from comparison
DescriptionDistributed and scalable native Graph DBMSEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformUltra-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.A fully ACID in-memory object graph database
Primary database modelGraph DBMSRelational DBMSDocument storeDocument storeDocument store
Object oriented DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.53
Rank#152  Overall
#15  Graph DBMS
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score0.60
Rank#244  Overall
#38  Document stores
Score0.06
Rank#380  Overall
#50  Document stores
#18  Object oriented DBMS
Websitedgraph.iowww.esgyn.cncloud.google.com/­datastorewww.harperdb.ioorigodb.com
Technical documentationdgraph.io/­docscloud.google.com/­datastore/­docsdocs.harperdb.io/­docsorigodb.com/­docs
DeveloperDgraph Labs, Inc.EsgynGoogleHarperDBRobert Friberg et al
Initial release20162015200820172009 infounder the name LiveDB
Current release3.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialcommercial infofree community edition availableOpen Source
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 languageGoC++, JavaNode.jsC#
Server operating systemsLinux
OS X
Windows
LinuxhostedLinux
OS X
Linux
Windows
Data schemeschema-freeyesschema-freedynamic schemayes
Typing infopredefined data types such as float or dateyesyesyes, details hereyes infoJSON data typesUser defined using .NET types and collections
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 infocan be achieved using .NET
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLnoyesSQL-like query language (GQL)SQL-like data manipulation statementsno
APIs and other access methodsGraphQL query language
gRPC (using protocol buffers) API
HTTP API
ADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
.NET Client API
HTTP API
LINQ
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All languages supporting JDBC/ODBC/ADO.Net.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.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
.Net
Server-side scripts infoStored proceduresnoJava Stored Proceduresusing Google App EngineCustom Functions infosince release 3.1yes
TriggersnonoCallbacks using the Google Apps Enginenoyes infoDomain Events
Partitioning methods infoMethods for storing different data on different nodesyesShardingShardingA table resides as a whole on one (or more) nodes in a clusterhorizontal partitioning infoclient side managed; servers are not synchronized
Replication methods infoMethods for redundantly storing data on multiple nodesSynchronous replication via RaftMulti-source replication between multi datacentersMulti-source replication using Paxosyes infothe nodes on which a table resides can be definedSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes 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 Consistency
Foreign keys infoReferential integritynoyesyes infovia ReferenceProperties or Ancestor pathsnodepending on model
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsAtomic execution of specific operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes, using LMDByes infoWrite ahead log
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
User concepts infoAccess controlno 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 rolesRole based authorization

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More resources
DgraphEsgynDBGoogle Cloud DatastoreHarperDBOrigoDB
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