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DBMS > Dgraph vs. EsgynDB vs. Google Cloud Bigtable vs. GridGain vs. Hazelcast

System Properties Comparison Dgraph vs. EsgynDB vs. Google Cloud Bigtable vs. GridGain vs. Hazelcast

Editorial information provided by DB-Engines
NameDgraph  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGridGain  Xexclude from comparisonHazelcast  Xexclude from comparison
DescriptionDistributed 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.GridGain is an in-memory computing platform, built on Apache IgniteA widely adopted in-memory data grid
Primary database modelGraph DBMSRelational DBMSKey-value store
Wide column store
Key-value store
Relational DBMS
Key-value store
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.48
Rank#158  Overall
#15  Graph DBMS
Score0.23
Rank#319  Overall
#141  Relational DBMS
Score3.58
Rank#92  Overall
#14  Key-value stores
#8  Wide column stores
Score1.53
Rank#155  Overall
#26  Key-value stores
#73  Relational DBMS
Score6.87
Rank#55  Overall
#6  Key-value stores
Websitedgraph.iowww.esgyn.cncloud.google.com/­bigtablewww.gridgain.comhazelcast.com
Technical documentationdgraph.io/­docscloud.google.com/­bigtable/­docswww.gridgain.com/­docs/­index.htmlhazelcast.org/­imdg/­docs
DeveloperDgraph Labs, Inc.EsgynGoogleGridGain Systems, Inc.Hazelcast
Initial release20162015201520072008
Current releaseGridGain 8.5.15.3.6, November 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialcommercialOpen Source infoApache Version 2; commercial licenses available
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++, JavaJava, C++, .NetJava
Server operating systemsLinux
OS X
Windows
LinuxhostedLinux
OS X
Solaris
Windows
All OS with a Java VM
Data schemeschema-freeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesnoyesyes
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.nononoyesyes infothe object must implement a serialization strategy
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLnoyesnoANSI-99 for query and DML statements, subset of DDLSQL-like query language
APIs and other access methodsGraphQL 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)
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JCache
JPA
Memcached protocol
RESTful HTTP API
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresnoJava Stored Proceduresnoyes (compute grid and cache interceptors can be used instead)yes infoEvent Listeners, Executor Services
Triggersnononoyes (cache interceptors and events)yes infoEvents
Partitioning methods infoMethods for storing different data on different nodesyesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSynchronous replication via RaftMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zonesyes (replicated cache)yes infoReplicated Map
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesyes (compute grid and hadoop accelerator)yes
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 ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithm
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDAtomic single-row operationsACIDone or two-phase-commit; repeatable reads; read commited
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.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)Security Hooks for custom implementationsRole-based access control

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More resources
DgraphEsgynDBGoogle Cloud BigtableGridGainHazelcast
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