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DBMS > Heroic vs. Ingres vs. LevelDB vs. Spark SQL

System Properties Comparison Heroic vs. Ingres vs. LevelDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameHeroic  Xexclude from comparisonIngres  Xexclude from comparisonLevelDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchWell established RDBMSEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelTime Series DBMSRelational DBMSKey-value storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Score3.80
Rank#82  Overall
#44  Relational DBMS
Score2.25
Rank#115  Overall
#19  Key-value stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­spotify/­heroicwww.actian.com/­databases/­ingresgithub.com/­google/­leveldbspark.apache.org/­sql
Technical documentationspotify.github.io/­heroicdocs.actian.com/­ingresgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperSpotifyActian CorporationGoogleApache Software Foundation
Initial release20141974 infooriginally developed at University Berkely in early 1970s20112014
Current release11.2, May 20221.23, February 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoBSDOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCC++Scala
Server operating systemsAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
Illumos
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
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.nono infobut tools for importing/exporting data from/to XML-files availablenono
Secondary indexesyes infovia Elasticsearchyesnono
SQL infoSupport of SQLnoyesnoSQL-like DML and DDL statements
APIs and other access methodsHQL (Heroic Query Language, a JSON-based language)
HTTP API
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
JDBC
ODBC
Supported programming languagesC++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyesnono
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslynoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesIngres Replicatornonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyes infoMVCCyesyes
Durability infoSupport for making data persistentyesyesyes infowith automatic compression on writesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlfine grained access rights according to SQL-standardnono

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HeroicIngresLevelDBSpark SQL
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