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DBMS > Apache Impala vs. Atos Standard Common Repository vs. Faircom EDGE vs. InterSystems Caché vs. ReductStore

System Properties Comparison Apache Impala vs. Atos Standard Common Repository vs. Faircom EDGE vs. InterSystems Caché vs. ReductStore

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonReductStore  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.
DescriptionAnalytic DBMS for HadoopHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsA multi-model DBMS and application serverDesigned to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.
Primary database modelRelational DBMSDocument store
Key-value store
Key-value store
Relational DBMS
Key-value store
Object oriented DBMS
Relational DBMS
Time Series DBMS
Secondary database modelsDocument storeDocument 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
Score0.05
Rank#384  Overall
#44  Time Series DBMS
Websiteimpala.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.faircom.com/­products/­faircom-edgewww.intersystems.com/­products/­cachegithub.com/­reductstore
www.reduct.store
Technical documentationimpala.apache.org/­impala-docs.htmldocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmldocs.intersystems.comwww.reduct.store/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaAtos Convergence CreatorsFairCom CorporationInterSystemsReductStore LLC
Initial release20132016197919972023
Current release4.1.0, June 20221703V3, October 20202018.1.4, May 20201.9, March 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercial infoRestricted, free version availablecommercialOpen Source infoBusiness Source License 1.1
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaANSI C, C++C++, Rust
Server operating systemsLinuxLinuxAndroid
Linux infoARM, x86
Raspbian
Windows
AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Docker
Linux
macOS
Windows
Data schemeyesSchema and schema-less with LDAP viewsFlexible Schema (defined schema, partial schema, schema free)depending on used data model
Typing infopredefined data types such as float or dateyesoptionalyes, 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.noyesyesyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyes infoANSI SQL queriesyes
APIs and other access methodsJDBC
ODBC
LDAPADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
.NET Client API
JDBC
ODBC
RESTful HTTP API
HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCAll languages with LDAP bindingsC
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C#
C++
Java
C++
JavaScript (Node.js)
Python
Rust
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyes info.Net, JavaScript, C/C++yes
Triggersnoyesyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infocell divisionFile partitioning infoCustomizable business rules for partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesyes infoSynchronous and asynchronous realtime replication based on transaction logsSource-replica replication
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 Consistency or Eventual Consistency depending on configurationImmediate Consistency
Tunable Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyes infowhen using SQLyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsACIDACID
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.noyesyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosLDAP bind authenticationFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Access rights for users, groups and roles

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More resources
Apache ImpalaAtos Standard Common RepositoryFaircom EDGE infoformerly c-treeEDGEInterSystems CachéReductStore
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