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DBMS > Apache Impala vs. Datastax Enterprise vs. Faircom EDGE vs. FoundationDB vs. Spark SQL

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

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatastax Enterprise  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonFoundationDB  Xexclude from comparisonSpark SQL  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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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 HadoopDataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.FairCom 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 processing
Primary database modelRelational DBMSWide column storeKey-value store
Relational DBMS
Document store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Relational DBMS
Secondary database modelsDocument storeDocument store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score5.80
Rank#60  Overall
#4  Wide column stores
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
Websiteimpala.apache.orgwww.datastax.com/­products/­datastax-enterprisewww.faircom.com/­products/­faircom-edgegithub.com/­apple/­foundationdbspark.apache.org/­sql
Technical documentationimpala.apache.org/­impala-docs.htmldocs.datastax.comdocs.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 ClouderaDataStaxFairCom CorporationFoundationDBApache Software Foundation
Initial release20132011197920132014
Current release4.1.0, June 20226.8, April 2020V3, October 20206.2.28, November 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercial infoRestricted, free version availableOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Datastax Astra DB: Astra DB simplifies cloud-native Cassandra application development for your apps, microservices and functions. Deploy in minutes on AWS, Google Cloud, Azure, and have it managed for you by the experts, with serverless, pay-as-you-go pricing.
Implementation languageC++JavaANSI C, C++C++Scala
Server operating systemsLinuxLinux
OS X
Android
Linux infoARM, x86
Raspbian
Windows
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeyesschema-freeFlexible Schema (defined schema, partial schema, schema free)schema-free infosome layers support schemasyes
Typing infopredefined data types such as float or dateyesyesyes, ANSI Standard SQL Typesno infosome layers support typingyes
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.nonoyesno
Secondary indexesyesyesyesnono
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like DML and DDL statements (CQL); Spark SQLyes infoANSI SQL queriessupported in specific SQL layer onlySQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
Proprietary protocol infoCQL (Cassandra Query Language)
TinkerPop Gremlin infowith DSE Graph
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/ODBCC
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyes info.Net, JavaScript, C/C++in SQL-layer onlyno
Triggersnoyesyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infono "single point of failure"File partitioning infoCustomizable business rules for partitioningShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorconfigurable replication factor, datacenter aware, advanced replication for edge computingyes infoSynchronous and asynchronous realtime replication based on transaction logsyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Tunable Consistency infoconsistency level can be individually decided with each write operation
Immediate Consistency
Tunable Consistency
Linearizable consistency
Foreign keys infoReferential integritynonoyes infowhen using SQLin SQL-layer onlyno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infoAtomicity and isolation are supported for single operationsACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoacross SQL and NoSQLyesyes
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.noyesyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users can be defined per objectFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.nono
More information provided by the system vendor
Apache ImpalaDatastax EnterpriseFaircom EDGE infoformerly c-treeEDGEFoundationDBSpark SQL
Specific characteristicsDataStax Enterprise is scale-out data infrastructure for enterprises that need to...
» more
Competitive advantagesSupporting the following application requirements: Zero downtime - Built on Apache...
» more
Typical application scenariosApplications that must be massively and linearly scalable with 100% uptime and able...
» more
Key customersCapital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
» more
Market metricsAmong the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
» more
Licensing and pricing modelsAnnual subscription
» more

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More resources
Apache ImpalaDatastax EnterpriseFaircom EDGE infoformerly c-treeEDGEFoundationDBSpark SQL
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