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DBMS > Apache Phoenix vs. Hazelcast vs. Kdb vs. LMDB vs. Spark SQL

System Properties Comparison Apache Phoenix vs. Hazelcast vs. Kdb vs. LMDB vs. Spark SQL

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonHazelcast  Xexclude from comparisonKdb  Xexclude from comparisonLMDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseA widely adopted in-memory data gridHigh performance Time Series DBMSA high performant, light-weight, embedded key-value database librarySpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSKey-value storeTime Series DBMS
Vector DBMS
Key-value storeRelational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score7.55
Rank#53  Overall
#3  Time Series DBMS
#1  Vector DBMS
Score1.99
Rank#125  Overall
#21  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitephoenix.apache.orghazelcast.comkx.comwww.symas.com/­symas-embedded-database-lmdbspark.apache.org/­sql
Technical documentationphoenix.apache.orghazelcast.org/­imdg/­docscode.kx.comwww.lmdb.tech/­docspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationHazelcastKx Systems, a division of First Derivatives plcSymasApache Software Foundation
Initial release201420082000 infokdb was released 2000, kdb+ in 200320112014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20195.3.6, November 20233.6, May 20180.9.32, January 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2; commercial licenses availablecommercial infofree 32-bit versionOpen SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaqCScala
Server operating systemsLinux
Unix
Windows
All OS with a Java VMLinux
OS X
Solaris
Windows
Linux
Unix
Windows
Linux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.noyes infothe object must implement a serialization strategyyesnono
Secondary indexesyesyesyes infotable attribute 'grouped'nono
SQL infoSupport of SQLyesSQL-like query languageSQL-like query language (q)noSQL-like DML and DDL statements
APIs and other access methodsJDBCJCache
JPA
Memcached protocol
RESTful HTTP API
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsyes infoEvent Listeners, Executor Servicesuser defined functionsnono
Triggersnoyes infoEventsyes infowith viewsnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioningnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yes infoReplicated MapSource-replica replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyesno infosimilar paradigm used for internal processingno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitednoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesyesno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyRole-based access controlrights management via user accountsnono
More information provided by the system vendor
Apache PhoenixHazelcastKdbLMDBSpark SQL
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
» more

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Apache PhoenixHazelcastKdbLMDBSpark SQL
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