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DBMS > Faircom EDGE vs. Fauna vs. Hive vs. LMDB vs. Tkrzw

System Properties Comparison Faircom EDGE vs. Fauna vs. Hive vs. LMDB vs. Tkrzw

Editorial information provided by DB-Engines
NameFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonFauna infopreviously named FaunaDB  Xexclude from comparisonHive  Xexclude from comparisonLMDB  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsFauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.data warehouse software for querying and managing large distributed datasets, built on HadoopA high performant, light-weight, embedded key-value database libraryA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelKey-value store
Relational DBMS
Document store
Graph DBMS
Relational DBMS
Time Series DBMS
Relational DBMSKey-value storeKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.02
Rank#368  Overall
#54  Key-value stores
#156  Relational DBMS
Score1.52
Rank#153  Overall
#26  Document stores
#14  Graph DBMS
#71  Relational DBMS
#13  Time Series DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score1.99
Rank#125  Overall
#21  Key-value stores
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitewww.faircom.com/­products/­faircom-edgefauna.comhive.apache.orgwww.symas.com/­symas-embedded-database-lmdbdbmx.net/­tkrzw
Technical documentationdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmldocs.fauna.comcwiki.apache.org/­confluence/­display/­Hive/­Homewww.lmdb.tech/­doc
DeveloperFairCom CorporationFauna, Inc.Apache Software Foundation infoinitially developed by FacebookSymasMikio Hirabayashi
Initial release19792014201220112020
Current releaseV3, October 20203.1.3, April 20220.9.32, January 20240.9.3, August 2020
License infoCommercial or Open Sourcecommercial infoRestricted, free version availablecommercialOpen Source infoApache Version 2Open SourceOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageANSI C, C++ScalaJavaCC++
Server operating systemsAndroid
Linux infoARM, x86
Raspbian
Windows
hostedAll OS with a Java VMLinux
Unix
Windows
Linux
macOS
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyes, ANSI Standard SQL Typesnoyesno
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.yesnonono
Secondary indexesyesyesyesno
SQL infoSupport of SQLyes infoANSI SQL queriesnoSQL-like DML and DDL statementsnono
APIs and other access methodsADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
RESTful HTTP APIJDBC
ODBC
Thrift
Supported programming languagesC
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift
C++
Java
PHP
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
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++user defined functionsyes infouser defined functions and integration of map-reducenono
Triggersyesnononono
Partitioning methods infoMethods for storing different data on different nodesFile partitioning infoCustomizable business rules for partitioninghorizontal partitioning infoconsistent hashingShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoSynchronous and asynchronous realtime replication based on transaction logsMulti-source replicationselectable replication factornonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Tunable Consistency
Immediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infowhen using SQLyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayes infoacross SQL and NoSQLyesyesyesyes
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.yesnoyesyes infousing specific database classes
User concepts infoAccess controlFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Identity management, authentication, and access controlAccess rights for users, groups and rolesnono

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More resources
Faircom EDGE infoformerly c-treeEDGEFauna infopreviously named FaunaDBHiveLMDBTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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