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DBMS > Heroic vs. LevelDB vs. Oracle Berkeley DB vs. Spark SQL vs. Teradata

System Properties Comparison Heroic vs. LevelDB vs. Oracle Berkeley DB vs. Spark SQL vs. Teradata

Editorial information provided by DB-Engines
NameHeroic  Xexclude from comparisonLevelDB  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesWidely used in-process key-value storeSpark SQL is a component on top of 'Spark Core' for structured data processingA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelTime Series DBMSKey-value storeKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Score2.25
Rank#115  Overall
#19  Key-value stores
Score2.01
Rank#126  Overall
#21  Key-value stores
#3  Native XML DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score44.87
Rank#22  Overall
#15  Relational DBMS
Websitegithub.com/­spotify/­heroicgithub.com/­google/­leveldbwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlspark.apache.org/­sqlwww.teradata.com
Technical documentationspotify.github.io/­heroicgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mddocs.oracle.com/­cd/­E17076_05/­html/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.teradata.com
DeveloperSpotifyGoogleOracle infooriginally developed by Sleepycat, which was acquired by OracleApache Software FoundationTeradata
Initial release20142011199420141984
Current release1.23, February 202118.1.40, May 20203.5.0 ( 2.13), September 2023Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoBSDOpen 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++C, Java, C++ (depending on the Berkeley DB edition)Scala
Server operating systemsIllumos
Linux
OS X
Windows
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Windows
hosted
Linux
Data schemeschema-freeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesnonoyesyes
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.nonoyes infoonly with the Berkeley DB XML editionnoyes
Secondary indexesyes infovia Elasticsearchnoyesnoyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLnonoyes infoSQL interfaced based on SQLite is availableSQL-like DML and DDL statementsyes infoSQL 2016 + extensions
APIs and other access methodsHQL (Heroic Query Language, a JSON-based language)
HTTP API
JDBC
ODBC
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesC++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
.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
Java
Python
R
Scala
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresnonononoyes infoUDFs, stored procedures, table functions in parallel
Triggersnonoyes infoonly for the SQL APInoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnonenoneyes, utilizing Spark CoreSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneSource-replica replicationnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infowith automatic compression on writesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlnononofine grained access rights according to SQL-standard

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HeroicLevelDBOracle Berkeley DBSpark SQLTeradata
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