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DBMS > Apache Impala vs. Apache Kylin vs. DuckDB vs. Faircom DB vs. Greenplum

System Properties Comparison Apache Impala vs. Apache Kylin vs. DuckDB vs. Faircom DB vs. Greenplum

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonApache Kylin  Xexclude from comparisonDuckDB  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonGreenplum  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 stackAn embeddable, in-process, column-oriented SQL OLAP RDBMSNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.
Primary database modelRelational DBMSRelational DBMSRelational DBMSKey-value store
Relational DBMS
Relational DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
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
Score4.57
Rank#74  Overall
#40  Relational DBMS
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score8.37
Rank#48  Overall
#30  Relational DBMS
Websiteimpala.apache.orgkylin.apache.orgduckdb.orgwww.faircom.com/­products/­faircom-dbgreenplum.org
Technical documentationimpala.apache.org/­impala-docs.htmlkylin.apache.org/­docsduckdb.org/­docsdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmldocs.greenplum.org
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software Foundation, originally contributed from eBay IncFairCom CorporationPivotal Software Inc.
Initial release20132015201819792005
Current release4.1.0, June 20223.1.0, July 20200.10, February 2024V12, November 20207.0.0, September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0Open Source infoMIT Licensecommercial infoRestricted, free version availableOpen Source infoApache 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++JavaC++ANSI C, C++
Server operating systemsLinuxLinuxserver-lessAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Linux
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.nonononoyes infosince Version 4.2
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsANSI SQL for queries (using Apache Calcite)yesyes, ANSI SQL with proprietary extensionsyes
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC
ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC
C# info3rd party driver
C++
Crystal info3rd party driver
Go info3rd party driver
Java
Lisp info3rd party driver
Python
R
Ruby info3rd party driver
Rust
Swift
Zig info3rd party driver
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
C
Java
Perl
Python
R
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyes info.Net, JavaScript, C/C++yes
Triggersnonoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDtunable from ACID to Eventually ConsistentACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyesyesYes, 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.nonoyesyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnoFine grained access rights according to SQL-standard with additional protections for filesfine grained access rights according to SQL-standard

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More resources
Apache ImpalaApache KylinDuckDBFaircom DB infoformerly c-treeACEGreenplum
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