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DBMS > Apache Phoenix vs. etcd vs. HarperDB vs. Spark SQL

System Properties Comparison Apache Phoenix vs. etcd vs. HarperDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonetcd  Xexclude from comparisonHarperDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseA distributed reliable key-value storeUltra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSKey-value storeDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score7.03
Rank#54  Overall
#5  Key-value stores
Score0.60
Rank#244  Overall
#38  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitephoenix.apache.orgetcd.io
github.com/­etcd-io/­etcd
www.harperdb.iospark.apache.org/­sql
Technical documentationphoenix.apache.orgetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
docs.harperdb.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationHarperDBApache Software Foundation
Initial release201420172014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20193.4, August 20193.1, August 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0commercial infofree community edition availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaGoNode.jsScala
Server operating systemsLinux
Unix
Windows
FreeBSD
Linux
Windows infoexperimental
Linux
OS X
Linux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freedynamic schemayes
Typing infopredefined data types such as float or dateyesnoyes infoJSON data typesyes
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.nononono
Secondary indexesyesnoyesno
SQL infoSupport of SQLyesnoSQL-like data manipulation statementsSQL-like DML and DDL statements
APIs and other access methodsJDBCgRPC
JSON over HTTP
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
JDBC
ODBC
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
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsnoCustom Functions infosince release 3.1no
Triggersnoyes, watching key changesnono
Partitioning methods infoMethods for storing different data on different nodesShardingA table resides as a whole on one (or more) nodes in a clusteryes, utilizing Spark Core
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 infothe nodes on which a table resides can be definednone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoAtomic execution of specific operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes, using LMDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancynoAccess rights for users and rolesno

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More resources
Apache PhoenixetcdHarperDBSpark SQL
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