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DBMS > Apache Impala vs. Brytlyt vs. Faircom EDGE vs. Spark SQL

System Properties Comparison Apache Impala vs. Brytlyt vs. Faircom EDGE vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonBrytlyt  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSKey-value store
Relational DBMS
Relational DBMS
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
Score0.38
Rank#276  Overall
#127  Relational DBMS
Score0.09
Rank#362  Overall
#53  Key-value stores
#155  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteimpala.apache.orgbrytlyt.iowww.faircom.com/­products/­faircom-edgespark.apache.org/­sql
Technical documentationimpala.apache.org/­impala-docs.htmldocs.brytlyt.iodocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaBrytlytFairCom CorporationApache Software Foundation
Initial release2013201619792014
Current release4.1.0, June 20225.0, August 2023V3, October 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercial infoRestricted, free version availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C, C++ and CUDAANSI C, C++Scala
Server operating systemsLinuxLinux
OS X
Windows
Android
Linux infoARM, x86
Raspbian
Windows
Linux
OS X
Windows
Data schemeyesyesFlexible Schema (defined schema, partial schema, schema free)yes
Typing infopredefined data types such as float or dateyesyesyes, ANSI Standard SQL Typesyes
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.noyes infospecific XML-type available, but no XML query functionality.yesno
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsyesyes infoANSI SQL queriesSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C++
Delphi
Java
Perl
Python
Tcl
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions infoin PL/pgSQLyes info.Net, JavaScript, C/C++no
Triggersnoyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingFile partitioning infoCustomizable business rules for partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationyes infoSynchronous and asynchronous realtime replication based on transaction logsnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Tunable Consistency
Foreign keys infoReferential integritynoyesyes infowhen using SQLno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoacross SQL and NoSQLyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.no

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More resources
Apache ImpalaBrytlytFaircom EDGE infoformerly c-treeEDGESpark SQL
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