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DBMS > FeatureBase vs. LevelDB vs. Sequoiadb vs. Spark SQL

System Properties Comparison FeatureBase vs. LevelDB vs. Sequoiadb vs. Spark SQL

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Editorial information provided by DB-Engines
NameFeatureBase  Xexclude from comparisonLevelDB  Xexclude from comparisonSequoiadb  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionReal-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.Embeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesNewSQL database with distributed OLTP and SQLSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSKey-value storeDocument store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.31
Rank#292  Overall
#135  Relational DBMS
Score2.25
Rank#115  Overall
#19  Key-value stores
Score0.50
Rank#258  Overall
#41  Document stores
#120  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.featurebase.comgithub.com/­google/­leveldbwww.sequoiadb.comspark.apache.org/­sql
Technical documentationdocs.featurebase.comgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdwww.sequoiadb.com/­en/­index.php?m=Files&a=indexspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperMolecula and Pilosa Open Source ContributorsGoogleSequoiadb Ltd.Apache Software Foundation
Initial release2017201120132014
Current release2022, May 20221.23, February 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoBSDOpen Source infoServer: AGPL; Client: Apache V2Open 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 languageGoC++C++Scala
Server operating systemsLinux
macOS
Illumos
Linux
OS X
Windows
LinuxLinux
OS X
Windows
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesnoyes infooid, date, timestamp, binary, regexyes
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 indexesnonoyesno
SQL infoSupport of SQLSQL queriesnoSQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsgRPC
JDBC
Kafka Connector
ODBC
proprietary protocol using JSONJDBC
ODBC
Supported programming languagesJava
Python
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
.Net
C++
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoJavaScriptno
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnoDocument is locked during a transactionno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes, using Linux fsyncyes infowith automatic compression on writesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlnosimple password-based access controlno

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More resources
FeatureBaseLevelDBSequoiadbSpark SQL
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