DB-EnginesExtremeDB: mitigate connectivity issues in a DBMSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Apache Impala vs. Atos Standard Common Repository vs. chDB vs. Greenplum vs. Hive

System Properties Comparison Apache Impala vs. Atos Standard Common Repository vs. chDB vs. Greenplum vs. Hive

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonchDB  Xexclude from comparisonGreenplum  Xexclude from comparisonHive  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionAnalytic DBMS for HadoopHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksAn embedded SQL OLAP Engine powered by ClickHouseAnalytic 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.data warehouse software for querying and managing large distributed datasets, built on Hadoop
Primary database modelRelational DBMSDocument store
Key-value store
Relational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument storeTime Series DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.00
Rank#383  Overall
#158  Relational DBMS
Score8.37
Rank#48  Overall
#30  Relational DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Websiteimpala.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositorygithub.com/­chdb-io/­chdbgreenplum.orghive.apache.org
Technical documentationimpala.apache.org/­impala-docs.htmldoc.chdb.iodocs.greenplum.orgcwiki.apache.org/­confluence/­display/­Hive/­Home
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaAtos Convergence CreatorsPivotal Software Inc.Apache Software Foundation infoinitially developed by Facebook
Initial release20132016202320052012
Current release4.1.0, June 202217037.0.0, September 20233.1.3, April 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoApache Version 2
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++JavaJava
Server operating systemsLinuxLinuxserver-lessLinuxAll OS with a Java VM
Data schemeyesSchema and schema-less with LDAP viewsyesyes
Typing infopredefined data types such as float or dateyesoptionalyesyes
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.noyesyes infosince Version 4.2
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoClose to ANSI SQL (SQL/JSON + extensions)yesSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
LDAPJDBC
ODBC
JDBC
ODBC
Thrift
Supported programming languagesAll languages supporting JDBC/ODBCAll languages with LDAP bindingsBun
C
C++
Go
JavaScript (Node.js)
Python
Rust
C
Java
Perl
Python
R
C++
Java
PHP
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyesyes infouser defined functions and integration of map-reduce
Triggersnoyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infocell divisionShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesSource-replica replicationselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.noyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosLDAP bind authenticationfine grained access rights according to SQL-standardAccess rights for users, groups and roles

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Apache ImpalaAtos Standard Common RepositorychDBGreenplumHive
DB-Engines blog posts

Why is Hadoop not listed in the DB-Engines Ranking?
13 May 2013, Paul Andlinger

show all

Recent citations in the news

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Hudi: Uber Engineeringā€™s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

Updates & Upserts in Hadoop Ecosystem with Apache Kudu
27 October 2017, KDnuggets

provided by Google News

VMware Greenplum on AWS: Parallel Postgres for Enterprise Analytics at Scale | Amazon Web Services
9 September 2019, AWS Blog

1. Introducing the Greenplum Database - Data Warehousing with Greenplum [Book]
6 December 2018, O'Reilly Media

RSA: EMC integrates Hadoop with Greenplum database
26 February 2013, DatacenterDynamics

Greenplum 6 ventures outside the analytic box
19 March 2019, ZDNet

Greenplum 6 review: Jack of all trades, master of some
7 November 2019, InfoWorld

provided by Google News

Apache Software Foundation Announces ApacheĀ® Hive 4.0
30 April 2024, GlobeNewswire

ASF Unveils the Next Evolution of Big Data Processing With the Launch of Hive 4.0
2 May 2024, Datanami

Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services
18 October 2023, AWS Blog

18 Top Big Data Tools and Technologies to Know About in 2024
24 January 2024, TechTarget

Elevate Your Career with In-Demand Hadoop Skills in 2024
30 April 2024, Simplilearn

provided by Google News



Share this page

Featured Products

SingleStore logo

The database to transact, analyze and contextualize your data in real time.
Try it today.

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Present your product here