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DBMS > Apache Phoenix vs. GigaSpaces vs. LMDB vs. RocksDB vs. Spark SQL

System Properties Comparison Apache Phoenix vs. GigaSpaces vs. LMDB vs. RocksDB vs. Spark SQL

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGigaSpaces  Xexclude from comparisonLMDB  Xexclude from comparisonRocksDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsA high performant, light-weight, embedded key-value database libraryEmbeddable persistent key-value store optimized for fast storage (flash and RAM)Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSDocument store
Object oriented DBMS infoValues are user defined objects
Key-value storeKey-value storeRelational DBMS
Secondary database modelsGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score1.99
Rank#125  Overall
#21  Key-value stores
Score3.65
Rank#85  Overall
#11  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitephoenix.apache.orgwww.gigaspaces.comwww.symas.com/­symas-embedded-database-lmdbrocksdb.orgspark.apache.org/­sql
Technical documentationphoenix.apache.orgdocs.gigaspaces.com/­latest/­landing.htmlwww.lmdb.tech/­docgithub.com/­facebook/­rocksdb/­wikispark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationGigaspaces TechnologiesSymasFacebook, Inc.Apache Software Foundation
Initial release20142000201120132014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 201915.5, September 20200.9.32, January 20248.11.4, April 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2; Commercial licenses availableOpen SourceOpen Source infoBSDOpen 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 languageJavaJava, C++, .NetCC++Scala
Server operating systemsLinux
Unix
Windows
Linux
macOS
Solaris
Windows
Linux
Unix
Windows
LinuxLinux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeschema-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.nono infoXML can be used for describing objects metadatanonono
Secondary indexesyesyesnonono
SQL infoSupport of SQLyesSQL-99 for query and DML statementsnonoSQL-like DML and DDL statements
APIs and other access methodsJDBCGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
C++ API
Java API
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
C++
Java
Python
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
C
C++
Go
Java
Perl
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsyesnonono
Triggersnoyes, event driven architecturenono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnonehorizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
noneyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyes infoMap-Reduce pattern can be built with XAP task executorsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDyesno
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 controlnonono

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More resources
Apache PhoenixGigaSpacesLMDBRocksDBSpark SQL
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