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DBMS > Badger vs. Google Cloud Datastore vs. Hive vs. Ignite vs. JSqlDb

System Properties Comparison Badger vs. Google Cloud Datastore vs. Hive vs. Ignite vs. JSqlDb

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHive  Xexclude from comparisonIgnite  Xexclude from comparisonJSqlDb  Xexclude from comparison
JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platformdata 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.JavaScript Query Language Database, stores JavaScript objects and primitives
Primary database modelKey-value storeDocument storeRelational DBMSKey-value store
Relational DBMS
Document store
Object oriented DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#320  Overall
#47  Key-value stores
Score4.36
Rank#72  Overall
#12  Document stores
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score3.11
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Websitegithub.com/­dgraph-io/­badgercloud.google.com/­datastorehive.apache.orgignite.apache.orgjsqldb.org (offline)
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgercloud.google.com/­datastore/­docscwiki.apache.org/­confluence/­display/­Hive/­Homeapacheignite.readme.io/­docs
DeveloperDGraph LabsGoogleApache Software Foundation infoinitially developed by FacebookApache Software FoundationKonrad von Backstrom
Initial release20172008201220152018
Current release3.1.3, April 2022Apache Ignite 2.60.8, December 2018
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoApache Version 2Open Source infoApache 2.0Open Source
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJavaC++, Java, .Net
Server operating systemsBSD
Linux
OS X
Solaris
Windows
hostedAll OS with a Java VMLinux
OS X
Solaris
Windows
Linux
macOS
Windows
Data schemeschema-freeschema-freeyesyesschema-free
Typing infopredefined data types such as float or datenoyes, details hereyesyesno
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.nonoyesno
Secondary indexesnoyesyesyesno
SQL infoSupport of SQLnoSQL-like query language (GQL)SQL-like DML and DDL statementsANSI-99 for query and DML statements, subset of DDLno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Supported programming languagesGo.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
PHP
Python
C#
C++
Java
PHP
Python
Ruby
Scala
JavaScript
Server-side scripts infoStored proceduresnousing Google App Engineyes infouser defined functions and integration of map-reduceyes (compute grid and cache interceptors can be used instead)functions in JavaScript
TriggersnoCallbacks using the Google Apps Enginenoyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication using Paxosselectable replication factoryes (replicated cache)none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyes infoquery execution via MapReduceyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate 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.Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infousing RocksDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlnoAccess 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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More resources
BadgerGoogle Cloud DatastoreHiveIgniteJSqlDb
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