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DBMS > Badger vs. Dgraph vs. EsgynDB vs. GigaSpaces vs. Google Cloud Bigtable

System Properties Comparison Badger vs. Dgraph vs. EsgynDB vs. GigaSpaces vs. Google Cloud Bigtable

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonDgraph  Xexclude from comparisonEsgynDB  Xexclude from comparisonGigaSpaces  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Distributed and scalable native Graph DBMSEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.
Primary database modelKey-value storeGraph DBMSRelational DBMSDocument store
Object oriented DBMS infoValues are user defined objects
Key-value store
Wide column store
Secondary database modelsGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
Score1.45
Rank#156  Overall
#15  Graph DBMS
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Websitegithub.com/­dgraph-io/­badgerdgraph.iowww.esgyn.cnwww.gigaspaces.comcloud.google.com/­bigtable
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdgraph.io/­docsdocs.gigaspaces.com/­latest/­landing.htmlcloud.google.com/­bigtable/­docs
DeveloperDGraph LabsDgraph Labs, Inc.EsgynGigaspaces TechnologiesGoogle
Initial release20172016201520002015
Current release15.5, September 2020
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache 2.0commercialOpen Source infoApache Version 2; Commercial licenses availablecommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoGoC++, JavaJava, C++, .Net
Server operating systemsBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
LinuxLinux
macOS
Solaris
Windows
hosted
Data schemeschema-freeschema-freeyesschema-freeschema-free
Typing infopredefined data types such as float or datenoyesyesyesno
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.nononono infoXML can be used for describing objects metadatano
Secondary indexesnoyesyesyesno
SQL infoSupport of SQLnonoyesSQL-99 for query and DML statementsno
APIs and other access methodsGraphQL query language
gRPC (using protocol buffers) API
HTTP API
ADO.NET
JDBC
ODBC
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Supported programming languagesGoC#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All languages supporting JDBC/ODBC/ADO.Net.Net
C++
Java
Python
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnonoJava Stored Proceduresyesno
Triggersnononoyes, event driven architectureno
Partitioning methods infoMethods for storing different data on different nodesnoneyesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSynchronous replication via RaftMulti-source replication between multi datacentersMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Internal replication in Colossus, and regional replication between two clusters in different zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyes infoMap-Reduce pattern can be built with XAP task executorsyes
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACIDAtomic single-row operations
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.nonoyesno
User concepts infoAccess controlnono infoPlanned for future releasesfine grained access rights according to SQL-standardRole-based access controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
BadgerDgraphEsgynDBGigaSpacesGoogle Cloud Bigtable
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