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DBMS > Badger vs. CockroachDB vs. Google Cloud Datastore vs. HBase

System Properties Comparison Badger vs. CockroachDB vs. Google Cloud Datastore vs. HBase

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonCockroachDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHBase  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformWide-column store based on Apache Hadoop and on concepts of BigTable
Primary database modelKey-value storeRelational DBMSDocument storeWide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
Score6.15
Rank#55  Overall
#33  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score30.50
Rank#26  Overall
#2  Wide column stores
Websitegithub.com/­dgraph-io/­badgerwww.cockroachlabs.comcloud.google.com/­datastorehbase.apache.org
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerwww.cockroachlabs.com/­docscloud.google.com/­datastore/­docshbase.apache.org/­book.html
DeveloperDGraph LabsCockroach LabsGoogleApache Software Foundation infoApache top-level project, originally developed by Powerset
Initial release2017201520082008
Current release24.1.0, May 20242.3.4, January 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache 2.0, commercial license availablecommercialOpen Source infoApache version 2
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoGoJava
Server operating systemsBSD
Linux
OS X
Solaris
Windows
Linux
macOS
Windows
hostedLinux
Unix
Windows infousing Cygwin
Data schemeschema-freedynamic schemaschema-freeschema-free, schema definition possible
Typing infopredefined data types such as float or datenoyesyes, details hereoptions to bring your own types, AVRO
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
Secondary indexesnoyesyesno
SQL infoSupport of SQLnoyes, wire compatible with PostgreSQLSQL-like query language (GQL)no
APIs and other access methodsJDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RESTful HTTP API
Thrift
Supported programming languagesGoC#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
Server-side scripts infoStored proceduresnonousing Google App Engineyes infoCoprocessors in Java
TriggersnonoCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning (by key range) infoall tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFTShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication using RAFTMulti-source replication using PaxosMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowyes
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate 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.Immediate Consistency or Eventual Consistency
Foreign keys infoReferential integritynoyesyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsSingle row ACID (across millions of columns)
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes
User concepts infoAccess controlnoRole-based access controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

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More resources
BadgerCockroachDBGoogle Cloud DatastoreHBase
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