DB-EnginesExtremeDB for everyone with an RTOSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Heroic vs. OpenQM vs. Oracle Berkeley DB vs. Trafodion vs. VelocityDB

System Properties Comparison Heroic vs. OpenQM vs. Oracle Berkeley DB vs. Trafodion vs. VelocityDB

Editorial information provided by DB-Engines
NameHeroic  Xexclude from comparisonOpenQM infoalso called QM  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonTrafodion  Xexclude from comparisonVelocityDB  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchQpenQM is a high-performance, self-tuning, multi-value DBMSWidely used in-process key-value storeTransactional SQL-on-Hadoop DBMSA .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)
Primary database modelTime Series DBMSMultivalue DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMSGraph DBMS
Object oriented DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score0.27
Rank#298  Overall
#10  Multivalue DBMS
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Score0.05
Rank#358  Overall
#36  Graph DBMS
#16  Object oriented DBMS
Websitegithub.com/­spotify/­heroicwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-open-qmwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmltrafodion.apache.orgvelocitydb.com
Technical documentationspotify.github.io/­heroicdocs.oracle.com/­cd/­E17076_05/­html/­index.htmltrafodion.apache.org/­documentation.htmlvelocitydb.com/­UserGuide
DeveloperSpotifyRocket Software, originally Martin PhillipsOracle infooriginally developed by Sleepycat, which was acquired by OracleApache Software Foundation, originally developed by HPVelocityDB Inc
Initial release20141993199420142011
Current release3.4-1218.1.40, May 20202.3.0, February 20197.x
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoGPLv2, extended commercial license availableOpen Source infocommercial license availableOpen Source infoApache 2.0commercial
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 languageJavaC, Java, C++ (depending on the Berkeley DB edition)C++, JavaC#
Server operating systemsAIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
LinuxAny that supports .NET
Data schemeschema-freeyes infowith some exceptionsschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyes
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 infoonly with the Berkeley DB XML editionnono
Secondary indexesyes infovia Elasticsearchyesyesyesyes
SQL infoSupport of SQLnonoyes infoSQL interfaced based on SQLite is availableyesno
APIs and other access methodsHQL (Heroic Query Language, a JSON-based language)
HTTP API
ADO.NET
JDBC
ODBC
.Net
Supported programming languages.Net
Basic
C
Java
Objective C
PHP
Python
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
All languages supporting JDBC/ODBC/ADO.Net.Net
Server-side scripts infoStored proceduresnoyesnoJava Stored Proceduresno
Triggersnoyesyes infoonly for the SQL APInoCallbacks are triggered when data changes
Partitioning methods infoMethods for storing different data on different nodesShardingyesnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesSource-replica replicationyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes infovia user defined functions and HBaseno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlAccess rights can be defined down to the item levelnofine grained access rights according to SQL-standardBased on Windows Authentication

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
HeroicOpenQM infoalso called QMOracle Berkeley DBTrafodionVelocityDB
Recent citations in the news

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

provided by Google News

ACM recognizes far-reaching technical achievements with special awards
26 May 2021, EurekAlert

Margo I. Seltzer | Berkman Klein Center
18 August 2020, Berkman Klein Center

Database Trends Report: SQL Beats NoSQL, MySQL Most Popular -- ADTmag
5 March 2019, ADT Magazine

How to store financial market data for backtesting
26 January 2019, Towards Data Science

The importance of bitcoin nodes and how to start one
9 May 2014, The Merkle News

provided by Google News

Evaluating HTAP Databases for Machine Learning Applications
2 November 2016, KDnuggets

Low-latency, distributed database architectures are critical for emerging fog applications
7 April 2022, Embedded Computing Design

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

Milvus logo

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

RaimaDB logo

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

SingleStore logo

Build AI apps with Vectors on SQL and JSON with milliseconds response times.
Try it today.

Neo4j logo

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

Present your product here