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DBMS > Apache Impala vs. Faircom EDGE vs. FoundationDB vs. Spark SQL vs. STSdb

System Properties Comparison Apache Impala vs. Faircom EDGE vs. FoundationDB vs. Spark SQL vs. STSdb

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonFoundationDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonSTSdb  Xexclude from comparison
Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.
DescriptionAnalytic DBMS for HadoopFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsOrdered key-value store. Core features are complimented by layers.Spark SQL is a component on top of 'Spark Core' for structured data processingKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelRelational DBMSKey-value store
Relational DBMS
Document store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Relational DBMSKey-value store
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
Score0.02
Rank#368  Overall
#54  Key-value stores
#156  Relational DBMS
Score1.03
Rank#190  Overall
#31  Document stores
#28  Key-value stores
#89  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.04
Rank#360  Overall
#52  Key-value stores
Websiteimpala.apache.orgwww.faircom.com/­products/­faircom-edgegithub.com/­apple/­foundationdbspark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4
Technical documentationimpala.apache.org/­impala-docs.htmldocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlapple.github.io/­foundationdbspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaFairCom CorporationFoundationDBApache Software FoundationSTS Soft SC
Initial release20131979201320142011
Current release4.1.0, June 2022V3, October 20206.2.28, November 20203.5.0 ( 2.13), September 20234.0.8, September 2015
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infoRestricted, free version availableOpen Source infoApache 2.0Open Source infoApache 2.0Open Source infoGPLv2, commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ANSI C, C++C++ScalaC#
Server operating systemsLinuxAndroid
Linux infoARM, x86
Raspbian
Windows
Linux
OS X
Windows
Linux
OS X
Windows
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-free infosome layers support schemasyesyes
Typing infopredefined data types such as float or dateyesyes, ANSI Standard SQL Typesno infosome layers support typingyesyes infoprimitive types and user defined types (classes)
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.noyesno
Secondary indexesyesyesnonono
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infoANSI SQL queriessupported in specific SQL layer onlySQL-like DML and DDL statementsno
APIs and other access methodsJDBC
ODBC
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
JDBC
ODBC
.NET Client API
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Java
JavaScript
PHP
Python
VB.Net
.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
Java
Python
R
Scala
C#
Java
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes info.Net, JavaScript, C/C++in SQL-layer onlynono
Triggersnoyesnonono
Partitioning methods infoMethods for storing different data on different nodesShardingFile partitioning infoCustomizable business rules for partitioningShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes infoSynchronous and asynchronous realtime replication based on transaction logsyesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Tunable Consistency
Linearizable consistency
Foreign keys infoReferential integritynoyes infowhen using SQLin SQL-layer onlynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDnono
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.noyesno
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.nonono

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More resources
Apache ImpalaFaircom EDGE infoformerly c-treeEDGEFoundationDBSpark SQLSTSdb
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