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DBMS > Apache Impala vs. Databricks vs. Faircom EDGE vs. FatDB vs. mSQL

System Properties Comparison Apache Impala vs. Databricks vs. Faircom EDGE vs. FatDB vs. mSQL

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatabricks  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonFatDB  Xexclude from comparisonmSQL infoMini SQL  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionAnalytic DBMS for HadoopThe 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 environmentsA .NET NoSQL DBMS that can integrate with and extend SQL Server.mSQL (Mini SQL) is a simple and lightweight RDBMS
Primary database modelRelational DBMSDocument store
Relational DBMS
Key-value store
Relational DBMS
Document store
Key-value store
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.02
Rank#368  Overall
#54  Key-value stores
#156  Relational DBMS
Score1.27
Rank#167  Overall
#77  Relational DBMS
Websiteimpala.apache.orgwww.databricks.comwww.faircom.com/­products/­faircom-edgehughestech.com.au/­products/­msql
Technical documentationimpala.apache.org/­impala-docs.htmldocs.databricks.comdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDatabricksFairCom CorporationFatCloudHughes Technologies
Initial release20132013197920121994
Current release4.1.0, June 2022V3, October 20204.4, October 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercial infoRestricted, free version availablecommercialcommercial infofree licenses can be provided
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ANSI C, C++C#C
Server operating systemsLinuxhostedAndroid
Linux infoARM, x86
Raspbian
Windows
WindowsAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)Flexible Schema (defined schema, partial schema, schema free)schema-freeyes
Typing infopredefined data types such as float or dateyesyes, ANSI Standard SQL Typesyesyes
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.noyesyesno
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementswith Databricks SQLyes infoANSI SQL queriesno infoVia inetgration in SQL ServerA subset of ANSI SQL is implemented infono subqueries, aggregate functions, views, foreign keys, triggers
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCPython
R
Scala
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C#C
C++
Delphi
Java
Perl
PHP
Tcl
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions and aggregatesyes info.Net, JavaScript, C/C++yes infovia applicationsno
Triggersnoyesyes infovia applicationsno
Partitioning methods infoMethods for storing different data on different nodesShardingFile partitioning infoCustomizable business rules for partitioningShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesyes infoSynchronous and asynchronous realtime replication based on transaction logsselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Tunable Consistency
Eventual Consistency
Immediate Consistency
none
Foreign keys infoReferential integritynoyes infowhen using SQLnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoacross SQL and NoSQLyesno
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.nonoyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.no infoCan implement custom security layer via applicationsno
More information provided by the system vendor
Apache ImpalaDatabricksFaircom EDGE infoformerly c-treeEDGEFatDBmSQL infoMini SQL
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Apache ImpalaDatabricksFaircom EDGE infoformerly c-treeEDGEFatDBmSQL infoMini SQL
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