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DBMS > Apache Phoenix vs. Kinetica vs. LMDB vs. RavenDB vs. Spark SQL

System Properties Comparison Apache Phoenix vs. Kinetica vs. LMDB vs. RavenDB vs. Spark SQL

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonKinetica  Xexclude from comparisonLMDB  Xexclude from comparisonRavenDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseFully vectorized database across both GPUs and CPUsA high performant, light-weight, embedded key-value database libraryOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSKey-value storeDocument storeRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score1.99
Rank#125  Overall
#21  Key-value stores
Score2.92
Rank#101  Overall
#18  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitephoenix.apache.orgwww.kinetica.comwww.symas.com/­symas-embedded-database-lmdbravendb.netspark.apache.org/­sql
Technical documentationphoenix.apache.orgdocs.kinetica.comwww.lmdb.tech/­docravendb.net/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationKineticaSymasHibernating RhinosApache Software Foundation
Initial release20142012201120102014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20197.1, August 20210.9.32, January 20245.4, July 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen SourceOpen Source infoAGPL version 3, commercial license availableOpen 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 languageJavaC, C++CC#Scala
Server operating systemsLinux
Unix
Windows
LinuxLinux
Unix
Windows
Linux
macOS
Raspberry Pi
Windows
Linux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
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 indexesyesyesnoyesno
SQL infoSupport of SQLyesSQL-like DML and DDL statementsnoSQL-like query language (RQL)SQL-like DML and DDL statements
APIs and other access methodsJDBCJDBC
ODBC
RESTful HTTP API
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C++
Java
JavaScript (Node.js)
Python
.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
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsuser defined functionsnoyesno
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangenoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replicationnoneMulti-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID, Cluster-wide transaction availableno
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.yesyes infoGPU vRAM or System RAMyesno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess rights for users and roles on table levelnoAuthorization levels configured per client per databaseno

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More resources
Apache PhoenixKineticaLMDBRavenDBSpark SQL
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