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DBMS > Dgraph vs. EJDB vs. EsgynDB vs. Google Cloud Bigtable vs. Ignite

System Properties Comparison Dgraph vs. EJDB vs. EsgynDB vs. Google Cloud Bigtable vs. Ignite

Editorial information provided by DB-Engines
NameDgraph  Xexclude from comparisonEJDB  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonIgnite  Xexclude from comparison
DescriptionDistributed and scalable native Graph DBMSEmbeddable document-store database library with JSON representation of queries (in MongoDB style)Enterprise-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.Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.
Primary database modelGraph DBMSDocument storeRelational DBMSKey-value store
Wide column store
Key-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.45
Rank#156  Overall
#15  Graph DBMS
Score0.27
Rank#297  Overall
#44  Document stores
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Websitedgraph.iogithub.com/­Softmotions/­ejdbwww.esgyn.cncloud.google.com/­bigtableignite.apache.org
Technical documentationdgraph.io/­docsgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mdcloud.google.com/­bigtable/­docsapacheignite.readme.io/­docs
DeveloperDgraph Labs, Inc.SoftmotionsEsgynGoogleApache Software Foundation
Initial release20162012201520152015
Current releaseApache Ignite 2.6
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoGPLv2commercialcommercialOpen Source infoApache 2.0
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 languageGoCC++, JavaC++, Java, .Net
Server operating systemsLinux
OS X
Windows
server-lessLinuxhostedLinux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyes infostring, integer, double, bool, date, object_idyesnoyes
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.nononoyes
Secondary indexesyesnoyesnoyes
SQL infoSupport of SQLnonoyesnoANSI-99 for query and DML statements, subset of DDL
APIs and other access methodsGraphQL query language
gRPC (using protocol buffers) API
HTTP API
in-process shared libraryADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
All languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnonoJava Stored Proceduresnoyes (compute grid and cache interceptors can be used instead)
Triggersnonononoyes (cache interceptors and events)
Partitioning methods infoMethods for storing different data on different nodesyesnoneShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSynchronous replication via RaftnoneMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zonesyes (replicated cache)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyesyes (compute grid and hadoop accelerator)
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integritynono infotypically not needed, however similar functionality with collection joins possibleyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDAtomic single-row operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/Write Lockingyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlno infoPlanned for future releasesnofine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Security Hooks for custom implementations

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More resources
DgraphEJDBEsgynDBGoogle Cloud BigtableIgnite
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