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DBMS > Apache Impala vs. Apache Kylin vs. Atos Standard Common Repository vs. EXASOL vs. Faircom DB

System Properties Comparison Apache Impala vs. Apache Kylin vs. Atos Standard Common Repository vs. EXASOL vs. Faircom DB

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonApache Kylin  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonEXASOL  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionAnalytic DBMS for HadoopA distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stackHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.
Primary database modelRelational DBMSRelational DBMSDocument store
Key-value store
Relational DBMSKey-value store
Relational DBMS
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
Score1.18
Rank#172  Overall
#79  Relational DBMS
Score1.99
Rank#124  Overall
#58  Relational DBMS
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Websiteimpala.apache.orgkylin.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.exasol.comwww.faircom.com/­products/­faircom-db
Technical documentationimpala.apache.org/­impala-docs.htmlkylin.apache.org/­docswww.exasol.com/­resourcesdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software Foundation, originally contributed from eBay IncAtos Convergence CreatorsExasolFairCom Corporation
Initial release20132015201620001979
Current release4.1.0, June 20223.1.0, July 20201703V12, November 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0commercialcommercialcommercial infoRestricted, free version available
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.
Implementation languageC++JavaJavaANSI C, C++
Server operating systemsLinuxLinuxLinuxAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Data schemeyesyesSchema and schema-less with LDAP viewsyesschema free, schema optional, schema required, partial schema,
Typing infopredefined data types such as float or dateyesyesoptionalyesyes, ANSI SQL Types, JSON, typed binary structures
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.nonoyesnono
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsANSI SQL for queries (using Apache Calcite)noyesyes, ANSI SQL with proprietary extensions
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
LDAP.Net
JDBC
ODBC
WebSocket
ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
Supported programming languagesAll languages supporting JDBC/ODBCAll languages with LDAP bindingsJava
Lua
Python
R
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenouser defined functionsyes info.Net, JavaScript, C/C++
Triggersnoyesyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infocell divisionShardingFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesyes infoHadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsACIDtunable from ACID to Eventually Consistent
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesYes, tunable from durable to delayed durability to in-memory
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosLDAP bind authenticationAccess rights for users, groups and roles according to SQL-standardFine grained access rights according to SQL-standard with additional protections for files

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More resources
Apache ImpalaApache KylinAtos Standard Common RepositoryEXASOLFaircom DB infoformerly c-treeACE
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