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. HarperDB vs. HBase vs. Hive vs. XTDB

System Properties Comparison Apache Impala vs. HarperDB vs. HBase vs. Hive vs. XTDB

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonHarperDB  Xexclude from comparisonHBase  Xexclude from comparisonHive  Xexclude from comparisonXTDB infoformerly named Crux  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopUltra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.Wide-column store based on Apache Hadoop and on concepts of BigTabledata warehouse software for querying and managing large distributed datasets, built on HadoopA general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelRelational DBMSDocument storeWide column storeRelational DBMSDocument store
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
Score0.55
Rank#248  Overall
#38  Document stores
Score30.50
Rank#26  Overall
#2  Wide column stores
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score0.11
Rank#343  Overall
#46  Document stores
Websiteimpala.apache.orgwww.harperdb.iohbase.apache.orghive.apache.orggithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.harperdb.io/­docshbase.apache.org/­book.htmlcwiki.apache.org/­confluence/­display/­Hive/­Homewww.xtdb.com/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaHarperDBApache Software Foundation infoApache top-level project, originally developed by PowersetApache Software Foundation infoinitially developed by FacebookJuxt Ltd.
Initial release20132017200820122019
Current release4.1.0, June 20223.1, August 20212.3.4, January 20213.1.3, April 20221.19, September 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infofree community edition availableOpen Source infoApache version 2Open Source infoApache Version 2Open Source infoMIT License
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++Node.jsJavaJavaClojure
Server operating systemsLinuxLinux
OS X
Linux
Unix
Windows infousing Cygwin
All OS with a Java VMAll OS with a Java 8 (and higher) VM
Linux
Data schemeyesdynamic schemaschema-free, schema definition possibleyesschema-free
Typing infopredefined data types such as float or dateyesyes infoJSON data typesoptions to bring your own types, AVROyesyes, extensible-data-notation format
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 indexesyesyesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like data manipulation statementsnoSQL-like DML and DDL statementslimited SQL, making use of Apache Calcite
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
Java API
RESTful HTTP API
Thrift
JDBC
ODBC
Thrift
HTTP REST
JDBC
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
C
C#
C++
Groovy
Java
PHP
Python
Scala
C++
Java
PHP
Python
Clojure
Java
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceCustom Functions infosince release 3.1yes infoCoprocessors in Javayes infouser defined functions and integration of map-reduceno
Triggersnonoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingA table resides as a whole on one (or more) nodes in a clusterShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes infothe nodes on which a table resides can be definedMulti-source replication
Source-replica replication
selectable replication factoryes, each node contains all data
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyesyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency or Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsSingle row ACID (across millions of columns)noACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes, using LMDByesyesyes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users and rolesAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAccess 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 ImpalaHarperDBHBaseHiveXTDB infoformerly named Crux
DB-Engines blog posts

Cloudera's HBase PaaS offering now supports Complex Transactions
11 August 2021,  Krishna Maheshwari (sponsor) 

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

show all

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

show all

Recent citations in the news

Apache Impala 4 Supports Operator Multi-Threading
29 July 2021, iProgrammer

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 Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

provided by Google News

Startups of the Year 2023: Meet HarperDB - A Database and Application Development Platform
22 June 2023, hackernoon.com

Unlocking immersive golfing experiences with AWS Wavelength | Amazon Web Services
29 November 2022, AWS Blog

HarperDB: An underdog SQL / NoSQL database | ZDNET
7 February 2018, ZDNet

HarperDB 4.0 Delivers Enterprise-Grade Global Application Development to Every Developer
17 January 2023, Markets Insider

HarperDB is More Than Just a Database: Here's Why
21 August 2021, hackernoon.com

provided by Google News

Best Practices from Rackspace for Modernizing a Legacy HBase/Solr Architecture Using AWS Services | Amazon Web ...
9 October 2023, AWS Blog

Less Components, Higher Performance: Apache Doris instead of ClickHouse, MySQL, Presto, and HBase
20 October 2023, hackernoon.com

HBase: The database big data left behind
6 May 2016, InfoWorld

What Is HBase? (Definition, Uses, Benefits, Features)
22 December 2022, Built In

HydraBase – The evolution of HBase@Facebook
5 June 2014, Facebook Engineering

provided by Google News

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

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

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

Apache Hive 4.0 Launches, Revolutionizing Data Management and Analysis
1 May 2024, MyChesCo

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

provided by Google News



Share this page

Featured Products

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

SingleStore logo

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

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