DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Hive vs. VoltDB vs. YottaDB

System Properties Comparison Hive vs. VoltDB vs. YottaDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonVoltDB  Xexclude from comparisonYottaDB  Xexclude from comparison
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopDistributed In-Memory NewSQL RDBMS infoUsed for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memoryA fast and solid embedded Key-value store
Primary database modelRelational DBMSRelational DBMSKey-value store
Secondary database modelsRelational DBMS infousing the Octo plugin
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score1.47
Rank#157  Overall
#73  Relational DBMS
Score0.28
Rank#306  Overall
#44  Key-value stores
Websitehive.apache.orgwww.voltdb.comyottadb.com
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.voltdb.comyottadb.com/­resources/­documentation
DeveloperApache Software Foundation infoinitially developed by FacebookVoltDB Inc.YottaDB, LLC
Initial release201220102001
Current release3.1.3, April 202211.3, April 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoAGPL for Community Edition, commercial license for Enterprise, AWS, and Pro EditionsOpen Source infoAGPL 3.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava, C++C
Server operating systemsAll OS with a Java VMLinux
OS X infofor development
Docker
Linux
Data schemeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesno
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.no
Secondary indexesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infoonly a subset of SQL 99by using the Octo plugin
APIs and other access methodsJDBC
ODBC
Thrift
Java API
JDBC
RESTful HTTP/JSON API
PostgreSQL wire protocol infousing the Octo plugin
Proprietary protocol
Supported programming languagesC++
Java
PHP
Python
C#
C++
Erlang infonot officially supported
Go
Java
JavaScript infoNode.js
PHP
Python
C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceJava
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication
Source-replica replication
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Foreign keys infoReferential integritynono infoFOREIGN KEY constraints are not supported
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoTransactions are executed single-threaded within stored proceduresoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyes infoData access is serialized by the server
Durability infoSupport for making data persistentyesyes infoSnapshots and command loggingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes
User concepts infoAccess controlAccess rights for users, groups and rolesUsers and roles with access to stored proceduresUsers and groups based on OS-security mechanisms

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
HiveVoltDBYottaDB
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 Software Foundation Announces Apache Hive 4.0
30 April 2024, Datanami

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

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

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

GC Tuning for Improved Presto Reliability
11 January 2024, Uber

provided by Google News

Unveiling Volt Active Data's game-changing approach to limitless app performance
16 October 2023, YourStory

 VoltDB Launches Active(N) Lossless Cross Data Center Replication
31 August 2021, PR Newswire

VoltDB Turns to Real-Time Analytics with NewSQL Database
30 January 2014, Datanami

VoltDB Upgrades Power, Security of Its In-Memory Database
1 February 2017, eWeek

VoltDB Adds Geospatial Support, Cross-Site Replication
28 January 2016, The New Stack

provided by Google News



Share this page

Featured Products

Milvus logo

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

Neo4j logo

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

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

Present your product here