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DBMS > Badger vs. JaguarDB vs. Pinecone vs. Spark SQL

System Properties Comparison Badger vs. JaguarDB vs. Pinecone vs. Spark SQL

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonJaguarDB  Xexclude from comparisonPinecone  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Performant, highly scalable DBMS for AI and IoT applicationsA managed, cloud-native vector databaseSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeKey-value store
Vector DBMS
Vector DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#320  Overall
#47  Key-value stores
Score0.06
Rank#381  Overall
#59  Key-value stores
#13  Vector DBMS
Score3.23
Rank#92  Overall
#2  Vector DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­dgraph-io/­badgerwww.jaguardb.comwww.pinecone.iospark.apache.org/­sql
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerwww.jaguardb.com/­support.htmldocs.pinecone.io/­docs/­overviewspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDGraph LabsDataJaguar, Inc.Pinecone Systems, IncApache Software Foundation
Initial release2017201520192014
Current release3.3 July 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoGPL V3.0commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoC++ infothe server part. Clients available in other languagesScala
Server operating systemsBSD
Linux
OS X
Solaris
Windows
LinuxhostedLinux
OS X
Windows
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or datenoyesString, Number, Booleanyes
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 indexesnoyesno
SQL infoSupport of SQLnoA subset of ANSI SQL is implemented infobut no views, foreign keys, triggersnoSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP APIJDBC
ODBC
Supported programming languagesGoC
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
PythonJava
Python
R
Scala
Server-side scripts infoStored proceduresnonono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononono
User concepts infoAccess controlnorights management via user accountsno

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BadgerJaguarDBPineconeSpark SQL
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