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

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

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonHBase  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsWide-column store based on Apache Hadoop and on concepts of BigTableSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSKey-value store
Relational DBMS
Wide column storeRelational 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
Score0.09
Rank#362  Overall
#53  Key-value stores
#155  Relational DBMS
Score27.97
Rank#26  Overall
#2  Wide column stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteimpala.apache.orgwww.faircom.com/­products/­faircom-edgehbase.apache.orgspark.apache.org/­sql
Technical documentationimpala.apache.org/­impala-docs.htmldocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlhbase.apache.org/­book.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaFairCom CorporationApache Software Foundation infoApache top-level project, originally developed by PowersetApache Software Foundation
Initial release2013197920082014
Current release4.1.0, June 2022V3, October 20202.3.4, January 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infoRestricted, free version availableOpen Source infoApache version 2Open 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++ANSI C, C++JavaScala
Server operating systemsLinuxAndroid
Linux infoARM, x86
Raspbian
Windows
Linux
Unix
Windows infousing Cygwin
Linux
OS X
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-free, schema definition possibleyes
Typing infopredefined data types such as float or dateyesyes, ANSI Standard SQL Typesoptions to bring your own types, AVROyes
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.noyesnono
Secondary indexesyesyesnono
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infoANSI SQL queriesnoSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C
C#
C++
Groovy
Java
PHP
Python
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes info.Net, JavaScript, C/C++yes infoCoprocessors in Javano
Triggersnoyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingFile partitioning infoCustomizable business rules for partitioningShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes infoSynchronous and asynchronous realtime replication based on transaction logsMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Tunable Consistency
Immediate Consistency or Eventual Consistency
Foreign keys infoReferential integritynoyes infowhen using SQLnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDSingle row ACID (across millions of columns)no
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyesyes
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.noyesyesno
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.Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACno

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More resources
Apache ImpalaFaircom EDGE infoformerly c-treeEDGEHBaseSpark SQL
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