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DBMS > Apache Doris vs. Apache Phoenix vs. Drizzle vs. Google Cloud Datastore

System Properties Comparison Apache Doris vs. Apache Phoenix vs. Drizzle vs. Google Cloud Datastore

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Editorial information provided by DB-Engines
NameApache Doris  Xexclude from comparisonApache Phoenix  Xexclude from comparisonDrizzle  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionAn MPP-based analytics DBMS embracing the MySQL protocolA scale-out RDBMS with evolutionary schema built on Apache HBaseMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform
Primary database modelRelational DBMSRelational DBMSRelational DBMSDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.60
Rank#247  Overall
#113  Relational DBMS
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Websitedoris.apache.org
github.com/­apache/­doris
phoenix.apache.orgcloud.google.com/­datastore
Technical documentationgithub.com/­apache/­doris/­wikiphoenix.apache.orgcloud.google.com/­datastore/­docs
DeveloperApache Software Foundation, originally contributed from BaiduApache Software FoundationDrizzle project, originally started by Brian AkerGoogle
Initial release2017201420082008
Current release1.2.2, February 20235.0-HBase2, July 2018 and 4.15-HBase1, December 20197.2.4, September 2012
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoGNU GPLcommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC++
Server operating systemsLinuxLinux
Unix
Windows
FreeBSD
Linux
OS X
hosted
Data schemeyesyes infolate-bound, schema-on-read capabilitiesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes, details here
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 SQLyesyesyes infowith proprietary extensionsSQL-like query language (GQL)
APIs and other access methodsJDBC
MySQL client
JDBCJDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Supported programming languagesJavaC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C
C++
Java
PHP
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functionsuser defined functionsnousing Google App Engine
Triggersnonono infohooks for callbacks inside the server can be used.Callbacks using the Google Apps Engine
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
Multi-source replication using Paxos
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoHadoop integrationnoyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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.
Foreign keys infoReferential integritynonoyesyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactions
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.noyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
Apache DorisApache PhoenixDrizzleGoogle Cloud Datastore
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