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DBMS > Apache Phoenix vs. etcd vs. Microsoft Azure SQL Database vs. Solr

System Properties Comparison Apache Phoenix vs. etcd vs. Microsoft Azure SQL Database vs. Solr

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonetcd  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseA distributed reliable key-value storeDatabase as a Service offering with high compatibility to Microsoft SQL ServerA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSKey-value storeRelational DBMSSearch engine
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score7.25
Rank#54  Overall
#5  Key-value stores
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websitephoenix.apache.orgetcd.io
github.com/­etcd-io/­etcd
azure.microsoft.com/­en-us/­products/­azure-sql/­databasesolr.apache.org
Technical documentationphoenix.apache.orgetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
docs.microsoft.com/­en-us/­azure/­azure-sqlsolr.apache.org/­resources.html
DeveloperApache Software FoundationMicrosoftApache Software Foundation
Initial release201420102006
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20193.4, August 2019V129.6.0, April 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0commercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGoC++Java
Server operating systemsLinux
Unix
Windows
FreeBSD
Linux
Windows infoexperimental
hostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesnoyesyes infosupports customizable data types and automatic typing
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.nonoyesyes
Secondary indexesyesnoyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyesnoyesSolr Parallel SQL Interface
APIs and other access methodsJDBCgRPC
JSON over HTTP
ADO.NET
JDBC
ODBC
Java API
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresuser defined functionsnoTransact SQLJava plugins
Triggersnoyes, watching key changesyesyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.yes, with always 3 replicas availableyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDoptimistic locking
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.yesnoyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancynofine grained access rights according to SQL-standardyes

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Apache PhoenixetcdMicrosoft Azure SQL Database infoformerly SQL AzureSolr
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