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DBMS > Apache Phoenix vs. BigchainDB vs. GridGain vs. LMDB vs. Spark SQL

System Properties Comparison Apache Phoenix vs. BigchainDB vs. GridGain vs. LMDB vs. Spark SQL

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonBigchainDB  Xexclude from comparisonGridGain  Xexclude from comparisonLMDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsGridGain is an in-memory computing platform, built on Apache IgniteA 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 DBMSDocument storeKey-value store
Relational DBMS
Key-value storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score0.79
Rank#212  Overall
#36  Document stores
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score1.99
Rank#125  Overall
#21  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitephoenix.apache.orgwww.bigchaindb.comwww.gridgain.comwww.symas.com/­symas-embedded-database-lmdbspark.apache.org/­sql
Technical documentationphoenix.apache.orgbigchaindb.readthedocs.io/­en/­latestwww.gridgain.com/­docs/­index.htmlwww.lmdb.tech/­docspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationGridGain Systems, Inc.SymasApache Software Foundation
Initial release20142016200720112014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 2019GridGain 8.5.10.9.32, January 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoAGPL v3commercialOpen SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaPythonJava, C++, .NetCScala
Server operating systemsLinux
Unix
Windows
LinuxLinux
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 dateyesnoyesyes
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.nonoyesnono
Secondary indexesyesyesnono
SQL infoSupport of SQLyesnoANSI-99 for query and DML statements, subset of DDLnoSQL-like DML and DDL statements
APIs and other access methodsJDBCCLI Client
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Go
Haskell
Java
JavaScript
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
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 (compute grid and cache interceptors can be used instead)nono
Triggersnoyes (cache interceptors and events)nono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
selectable replication factoryes (replicated cache)nonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnoyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes,with MongoDB ord RethinkDByesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyyesSecurity Hooks for custom implementationsnono

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Apache PhoenixBigchainDBGridGainLMDBSpark SQL
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