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DBMS > Apache Impala vs. Apache Kylin vs. Apache Pinot vs. Faircom DB vs. GeoMesa

System Properties Comparison Apache Impala vs. Apache Kylin vs. Apache Pinot vs. Faircom DB vs. GeoMesa

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonApache Kylin  Xexclude from comparisonApache Pinot  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonGeoMesa  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stackRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.
Primary database modelRelational DBMSRelational DBMSRelational DBMSKey-value store
Relational DBMS
Spatial 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
Score1.25
Rank#170  Overall
#77  Relational DBMS
Score0.38
Rank#275  Overall
#126  Relational DBMS
Score0.29
Rank#304  Overall
#43  Key-value stores
#136  Relational DBMS
Score0.86
Rank#205  Overall
#4  Spatial DBMS
Websiteimpala.apache.orgkylin.apache.orgpinot.apache.orgwww.faircom.com/­products/­faircom-dbwww.geomesa.org
Technical documentationimpala.apache.org/­impala-docs.htmlkylin.apache.org/­docsdocs.pinot.apache.orgdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlwww.geomesa.org/­documentation/­stable/­user/­index.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software Foundation, originally contributed from eBay IncApache Software Foundation and contributorsFairCom CorporationCCRi and others
Initial release20132015201519792014
Current release4.1.0, June 20223.1.0, July 20201.0.0, September 2023V12, November 20205.0.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0Open Source infoApache Version 2.0commercial infoRestricted, free version availableOpen Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaJavaANSI C, C++Scala
Server operating systemsLinuxLinuxAll OS with a Java JDK11 or higherAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Data schemeyesyesyesschema free, schema optional, schema required, partial schema,yes
Typing infopredefined data types such as float or dateyesyesyesyes, ANSI SQL Types, JSON, typed binary structuresyes
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.nononono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsANSI SQL for queries (using Apache Calcite)SQL-like query languageyes, ANSI SQL with proprietary extensionsno
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
JDBCADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
Supported programming languagesAll languages supporting JDBC/ODBCGo
Java
Python
.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-reduceyes info.Net, JavaScript, C/C++no
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningdepending on storage layer
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).depending on storage layer
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
depending on storage layer
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanotunable from ACID to Eventually Consistentno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesYes, tunable from durable to delayed durability to in-memoryyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesdepending on storage layer
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosFine grained access rights according to SQL-standard with additional protections for filesyes infodepending on the DBMS used for storage

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More resources
Apache ImpalaApache KylinApache PinotFaircom DB infoformerly c-treeACEGeoMesa
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