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DBMS > Apache Phoenix vs. Google Cloud Datastore vs. Hive vs. Immudb

System Properties Comparison Apache Phoenix vs. Google Cloud Datastore vs. Hive vs. Immudb

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHive  Xexclude from comparisonImmudb  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 Platformdata warehouse software for querying and managing large distributed datasets, built on HadoopAn open source immutable (append-only) database with cryptographic verification which makes it tamper-resistant and fully auditable.
Primary database modelRelational DBMSDocument storeRelational DBMSKey-value store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score0.31
Rank#295  Overall
#42  Key-value stores
Websitephoenix.apache.orgcloud.google.com/­datastorehive.apache.orggithub.com/­codenotary/­immudb
immudb.io
Technical documentationphoenix.apache.orgcloud.google.com/­datastore/­docscwiki.apache.org/­confluence/­display/­Hive/­Homedocs.immudb.io
DeveloperApache Software FoundationGoogleApache Software Foundation infoinitially developed by FacebookCodenotary
Initial release2014200820122020
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20193.1.3, April 20221.2.3, April 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaGo
Server operating systemsLinux
Unix
Windows
hostedAll OS with a Java VMBSD
Linux
macOS
Solaris
Windows
z/OS
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyes, details hereyes
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.nonono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyesSQL-like query language (GQL)SQL-like DML and DDL statementsSQL-like syntax
APIs and other access methodsJDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
gRPC protocol
PostgreSQL wire protocol
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
PHP
Python
.Net
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functionsusing Google App Engineyes infouser defined functions and integration of map-reduceno
TriggersnoCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication using Paxosselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyes infousing Google Cloud Dataflowyes infoquery execution via MapReduceno
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 Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID
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.yesnono
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)Access rights for users, groups and roles

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More resources
Apache PhoenixGoogle Cloud DatastoreHiveImmudb
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