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DBMS > Apache Phoenix vs. Dragonfly vs. SingleStore

System Properties Comparison Apache Phoenix vs. Dragonfly vs. SingleStore

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonDragonfly  Xexclude from comparisonSingleStore infoformer name was MemSQL  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseA drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instanceMySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type
Primary database modelRelational DBMSKey-value storeRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.02
Rank#130  Overall
#63  Relational DBMS
Score0.42
Rank#271  Overall
#38  Key-value stores
Score5.91
Rank#61  Overall
#34  Relational DBMS
Websitephoenix.apache.orggithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
www.singlestore.com
Technical documentationphoenix.apache.orgwww.dragonflydb.io/­docsdocs.singlestore.com
DeveloperApache Software FoundationDragonflyDB team and community contributorsSingleStore Inc.
Initial release201420232013
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20191.0, March 20238.5, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoBSL 1.1commercial infofree developer edition available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities
Implementation languageJavaC++C++, Go
Server operating systemsLinux
Unix
Windows
LinuxLinux info64 bit version required
Data schemeyes infolate-bound, schema-on-read capabilitiesscheme-freeyes
Typing infopredefined data types such as float or dateyesstrings, hashes, lists, sets, sorted sets, bit arraysyes
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 indexesyesnoyes
SQL infoSupport of SQLyesnoyes infobut no triggers and foreign keys
APIs and other access methodsJDBCProprietary protocol infoRESP - REdis Serialization ProtocolCluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl
Bash
C
C#
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functionsLuayes
Triggersnopublish/subscribe channels provide some trigger functionalityno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infohash partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replicationSource-replica replication infostores two copies of each physical data partition on two separate nodes
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnono infocan define user-defined aggregate functions for map-reduce-style calculations
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic execution of command blocks and scriptsACID
Concurrency infoSupport for concurrent manipulation of datayesyes, strict serializability by the serveryes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes infoAll updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyPassword-based authenticationFine grained access control via users, groups and roles
More information provided by the system vendor
Apache PhoenixDragonflySingleStore infoformer name was MemSQL
Specific characteristicsSingleStore offers a fully-managed , distributed, highly-scalable SQL database designed...
» more
Competitive advantagesSingleStore’s competitive advantages include: Easy and Simplified Architecture with...
» more
Typical application scenariosDriving Fast Analytics: SingleStore delivers the fastest and most scalable reporting...
» more
Key customersIEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,...
» more
Market metricsCustomers in various industries worldwide including US and International Industry...
» more
Licensing and pricing modelsF ree Tier and Enterprise Edition
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Apache PhoenixDragonflySingleStore infoformer name was MemSQL
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Recent citations in the news

Supercharge SQL on Your Data in Apache HBase with Apache Phoenix | Amazon Web Services
2 June 2016, AWS Blog

Bridge the SQL-NoSQL gap with Apache Phoenix
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