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DBMS > Apache Phoenix vs. Badger vs. Datomic vs. Google Cloud Datastore vs. Quasardb

System Properties Comparison Apache Phoenix vs. Badger vs. Datomic vs. Google Cloud Datastore vs. Quasardb

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonBadger  Xexclude from comparisonDatomic  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonQuasardb  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDistributed, high-performance timeseries database
Primary database modelRelational DBMSKey-value storeRelational DBMSDocument storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score0.14
Rank#331  Overall
#49  Key-value stores
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Websitephoenix.apache.orggithub.com/­dgraph-io/­badgerwww.datomic.comcloud.google.com/­datastorequasar.ai
Technical documentationphoenix.apache.orggodoc.org/­github.com/­dgraph-io/­badgerdocs.datomic.comcloud.google.com/­datastore/­docsdoc.quasar.ai/­master
DeveloperApache Software FoundationDGraph LabsCognitectGooglequasardb
Initial release20142017201220082009
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20191.0.6735, June 20233.14.1, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0commercial infolimited edition freecommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licenses
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGoJava, ClojureC++
Server operating systemsLinux
Unix
Windows
BSD
Linux
OS X
Solaris
Windows
All OS with a Java VMhostedBSD
Linux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesnoyesyes, details hereyes infointeger and binary
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.nonononono
Secondary indexesyesnoyesyesyes infowith tags
SQL infoSupport of SQLyesnonoSQL-like query language (GQL)SQL-like query language
APIs and other access methodsJDBCRESTful HTTP APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
GoClojure
Java
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresuser defined functionsnoyes infoTransaction Functionsusing Google App Engineno
TriggersnonoBy using transaction functionsCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesShardingnonenone infoBut extensive use of caching in the application peersShardingSharding infoconsistent hashing
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
nonenone infoBut extensive use of caching in the application peersMulti-source replication using PaxosSource-replica replication with selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnonoyes infousing Google Cloud Dataflowwith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencynoneImmediate 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
Foreign keys infoReferential integritynononoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes infoby using LevelDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes inforecommended only for testing and developmentnoyes infoTransient mode
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancynonoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Cryptographically strong user authentication and audit trail

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More resources
Apache PhoenixBadgerDatomicGoogle Cloud DatastoreQuasardb
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