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DBMS > Databricks vs. Faircom EDGE vs. Fauna vs. GridGain vs. Tkrzw

System Properties Comparison Databricks vs. Faircom EDGE vs. Fauna vs. GridGain vs. Tkrzw

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonFauna infopreviously named FaunaDB  Xexclude from comparisonGridGain  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.FairCom 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.GridGain is an in-memory computing platform, built on Apache IgniteA 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 modelDocument store
Relational DBMS
Key-value store
Relational DBMS
Document store
Graph DBMS
Relational DBMS
Time Series DBMS
Key-value store
Relational DBMS
Key-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
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
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitewww.databricks.comwww.faircom.com/­products/­faircom-edgefauna.comwww.gridgain.comdbmx.net/­tkrzw
Technical documentationdocs.databricks.comdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmldocs.fauna.comwww.gridgain.com/­docs/­index.html
DeveloperDatabricksFairCom CorporationFauna, Inc.GridGain Systems, Inc.Mikio Hirabayashi
Initial release20131979201420072020
Current releaseV3, October 2020GridGain 8.5.10.9.3, August 2020
License infoCommercial or Open Sourcecommercialcommercial infoRestricted, free version availablecommercialcommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageANSI C, C++ScalaJava, C++, .NetC++
Server operating systemshostedAndroid
Linux infoARM, x86
Raspbian
Windows
hostedLinux
OS X
Solaris
Windows
Linux
macOS
Data schemeFlexible Schema (defined schema, partial schema, schema free)Flexible Schema (defined schema, partial schema, schema free)schema-freeyesschema-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.yesyesnoyesno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLwith Databricks SQLyes infoANSI SQL queriesnoANSI-99 for query and DML statements, subset of DDLno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
RESTful HTTP APIHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Supported programming languagesPython
R
Scala
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift
C#
C++
Java
PHP
Python
Ruby
Scala
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes info.Net, JavaScript, C/C++user defined functionsyes (compute grid and cache interceptors can be used instead)no
Triggersyesnoyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesFile partitioning infoCustomizable business rules for partitioninghorizontal partitioning infoconsistent hashingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoSynchronous and asynchronous realtime replication based on transaction logsMulti-source replicationyes (replicated cache)none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Tunable Consistency
Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infowhen using SQLyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyesyesyes
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.noyesnoyesyes 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 controlSecurity Hooks for custom implementationsno
More information provided by the system vendor
DatabricksFaircom EDGE infoformerly c-treeEDGEFauna infopreviously named FaunaDBGridGainTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksFaircom EDGE infoformerly c-treeEDGEFauna infopreviously named FaunaDBGridGainTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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