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

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

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatabricks  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonFatDB  Xexclude from comparisonRealm  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.A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data
Primary database modelRelational DBMSDocument store
Relational DBMS
Key-value store
Relational DBMS
Document store
Key-value store
Document store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.09
Rank#362  Overall
#53  Key-value stores
#155  Relational DBMS
Score7.41
Rank#52  Overall
#8  Document stores
Websiteimpala.apache.orgwww.databricks.comwww.faircom.com/­products/­faircom-edgerealm.io
Technical documentationimpala.apache.org/­impala-docs.htmldocs.databricks.comdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlrealm.io/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDatabricksFairCom CorporationFatCloudRealm, acquired by MongoDB in May 2019
Initial release20132013197920122014
Current release4.1.0, June 2022V3, October 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercial infoRestricted, free version availablecommercialOpen Source
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#
Server operating systemsLinuxhostedAndroid
Linux infoARM, x86
Raspbian
Windows
WindowsAndroid
Backend: server-less
iOS
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 Serverno
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
Supported programming languagesAll languages supporting JDBC/ODBCPython
R
Scala
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C#.Net
Java infowith Android only
Objective-C
React Native
Swift
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 inforuns within the applications so server-side scripts are unnecessary
Triggersnoyesyes infovia applicationsyes infoChange Listeners
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
Immediate Consistency
Foreign keys infoReferential integritynoyes infowhen using SQLnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoacross SQL and NoSQLyes
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.nonoyesyes infoIn-Memory realm
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 applicationsyes
More information provided by the system vendor
Apache ImpalaDatabricksFaircom EDGE infoformerly c-treeEDGEFatDBRealm
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Apache ImpalaDatabricksFaircom EDGE infoformerly c-treeEDGEFatDBRealm
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