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DBMS > Apache Phoenix vs. Google Cloud Datastore vs. JaguarDB vs. Microsoft Azure Table Storage vs. Sequoiadb

System Properties Comparison Apache Phoenix vs. Google Cloud Datastore vs. JaguarDB vs. Microsoft Azure Table Storage vs. Sequoiadb

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonJaguarDB  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonSequoiadb  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformPerformant, highly scalable DBMS for AI and IoT applicationsA Wide Column Store for rapid development using massive semi-structured datasetsNewSQL database with distributed OLTP and SQL
Primary database modelRelational DBMSDocument storeKey-value store
Vector DBMS
Wide column storeDocument store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score0.00
Rank#383  Overall
#60  Key-value stores
#13  Vector DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Score0.45
Rank#261  Overall
#41  Document stores
#122  Relational DBMS
Websitephoenix.apache.orgcloud.google.com/­datastorewww.jaguardb.comazure.microsoft.com/­en-us/­services/­storage/­tableswww.sequoiadb.com
Technical documentationphoenix.apache.orgcloud.google.com/­datastore/­docswww.jaguardb.com/­support.htmlwww.sequoiadb.com/­en/­index.php?m=Files&a=index
DeveloperApache Software FoundationGoogleDataJaguar, Inc.MicrosoftSequoiadb Ltd.
Initial release20142008201520122013
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20193.3 July 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoGPL V3.0commercialOpen Source infoServer: AGPL; Client: Apache V2
Cloud-based only infoOnly available as a cloud servicenoyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++ infothe server part. Clients available in other languagesC++
Server operating systemsLinux
Unix
Windows
hostedLinuxhostedLinux
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyes, details hereyesyesyes infooid, date, timestamp, binary, regex
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 indexesyesyesyesnoyes
SQL infoSupport of SQLyesSQL-like query language (GQL)A subset of ANSI SQL is implemented infobut no views, foreign keys, triggersnoSQL-like query language
APIs and other access methodsJDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP APIproprietary protocol using JSON
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C++
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functionsusing Google App EnginenonoJavaScript
TriggersnoCallbacks using the Google Apps Enginenonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication using PaxosMulti-source replicationyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyes infousing Google Cloud Dataflownonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual 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.Eventual ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnooptimistic lockingDocument is locked during a transaction
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.yesnononono
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)rights management via user accountsAccess rights based on private key authentication or shared access signaturessimple password-based access control

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More resources
Apache PhoenixGoogle Cloud DatastoreJaguarDBMicrosoft Azure Table StorageSequoiadb
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