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

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

Editorial information provided by DB-Engines
NameDgraph  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHive  Xexclude from comparisonIgnite  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.data warehouse software for querying and managing large distributed datasets, built on HadoopApache 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 DBMSRelational DBMSKey-value store
Wide column store
Relational DBMSKey-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
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Websitedgraph.iowww.esgyn.cncloud.google.com/­bigtablehive.apache.orgignite.apache.org
Technical documentationdgraph.io/­docscloud.google.com/­bigtable/­docscwiki.apache.org/­confluence/­display/­Hive/­Homeapacheignite.readme.io/­docs
DeveloperDgraph Labs, Inc.EsgynGoogleApache Software Foundation infoinitially developed by FacebookApache Software Foundation
Initial release20162015201520122015
Current release3.1.3, April 2022Apache Ignite 2.6
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialOpen Source infoApache Version 2Open Source infoApache 2.0
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++, JavaJavaC++, Java, .Net
Server operating systemsLinux
OS X
Windows
LinuxhostedAll OS with a Java VMLinux
OS X
Solaris
Windows
Data schemeschema-freeyesschema-freeyesyes
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.nononoyes
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLnoyesnoSQL-like DML and DDL statementsANSI-99 for query and DML statements, subset of DDL
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)
JDBC
ODBC
Thrift
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
All languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Java
PHP
Python
C#
C++
Java
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnoJava Stored Proceduresnoyes infouser defined functions and integration of map-reduceyes (compute grid and cache interceptors can be used instead)
Triggersnonononoyes (cache interceptors and events)
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 zonesselectable replication factoryes (replicated cache)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesyes infoquery execution via MapReduceyes (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)Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDAtomic single-row operationsnoACID
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.nonoyes
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, groups and rolesSecurity Hooks for custom implementations

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DgraphEsgynDBGoogle Cloud BigtableHiveIgnite
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