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DBMS > Apache Phoenix vs. Badger vs. Google Cloud Datastore vs. Microsoft Azure SQL Database vs. UniData,UniVerse

System Properties Comparison Apache Phoenix vs. Badger vs. Google Cloud Datastore vs. Microsoft Azure SQL Database vs. UniData,UniVerse

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonBadger  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonUniData,UniVerse  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.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDatabase as a Service offering with high compatibility to Microsoft SQL ServerMultiValue database and application server with SQL mapping layer and meta database capabilities
Primary database modelRelational DBMSKey-value storeDocument storeRelational DBMSMultivalue DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial 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
Score4.47
Rank#76  Overall
#12  Document stores
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score3.16
Rank#97  Overall
#2  Multivalue DBMS
Websitephoenix.apache.orggithub.com/­dgraph-io/­badgercloud.google.com/­datastoreazure.microsoft.com/­en-us/­products/­azure-sql/­databasewww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-unidata
Technical documentationphoenix.apache.orggodoc.org/­github.com/­dgraph-io/­badgercloud.google.com/­datastore/­docsdocs.microsoft.com/­en-us/­azure/­azure-sqldocs.rocketsoftware.com/­bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata
DeveloperApache Software FoundationDGraph LabsGoogleMicrosoftRocket Software
Initial release20142017200820101985
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 2019V12
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGoC++C
Server operating systemsLinux
Unix
Windows
BSD
Linux
OS X
Solaris
Windows
hostedhostedAIX
HP-UX
Linux
Solaris
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesnoyes, details hereyesoptional
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 indexesyesnoyesyesyes
SQL infoSupport of SQLyesnoSQL-like query language (GQL)yesyes
APIs and other access methodsJDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
Java API infoJPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Go.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Basic infoU2 Basic
C
Java
Server-side scripts infoStored proceduresuser defined functionsnousing Google App EngineTransact SQLyes
TriggersnonoCallbacks using the Google Apps Engineyesyes infoU2 Basic
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
noneMulti-source replication using Paxosyes, with always 3 replicas availableSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencynoneImmediate 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 integritynonoyes infovia ReferenceProperties or Ancestor pathsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID infoconfigurable
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.yesnono
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancynoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardAccess rights according to SQL-standard and operating system based

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More resources
Apache PhoenixBadgerGoogle Cloud DatastoreMicrosoft Azure SQL Database infoformerly SQL AzureUniData,UniVerse
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