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DBMS > DuckDB vs. JaguarDB vs. Kinetica vs. Solr vs. Sqrrl

System Properties Comparison DuckDB vs. JaguarDB vs. Kinetica vs. Solr vs. Sqrrl

Editorial information provided by DB-Engines
NameDuckDB  Xexclude from comparisonJaguarDB  Xexclude from comparisonKinetica  Xexclude from comparisonSolr  Xexclude from comparisonSqrrl  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionAn embeddable, in-process, column-oriented SQL OLAP RDBMSPerformant, highly scalable DBMS for AI and IoT applicationsFully vectorized database across both GPUs and CPUsA widely used distributed, scalable search engine based on Apache LuceneAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelRelational DBMSKey-value store
Vector DBMS
Relational DBMSSearch engineDocument store
Graph DBMS
Key-value store
Wide column store
Secondary database modelsSpatial DBMS
Time Series DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.57
Rank#74  Overall
#40  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
#13  Vector DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websiteduckdb.orgwww.jaguardb.comwww.kinetica.comsolr.apache.orgsqrrl.com
Technical documentationduckdb.org/­docswww.jaguardb.com/­support.htmldocs.kinetica.comsolr.apache.org/­resources.html
DeveloperDataJaguar, Inc.KineticaApache Software FoundationAmazon infooriginally Sqrrl Data, Inc.
Initial release20182015201220062012
Current release0.10, February 20243.3 July 20237.1, August 20219.6.0, April 2024
License infoCommercial or Open SourceOpen Source infoMIT LicenseOpen Source infoGPL V3.0commercialOpen Source infoApache Version 2commercial
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 languageC++C++ infothe server part. Clients available in other languagesC, C++JavaJava
Server operating systemsserver-lessLinuxLinuxAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
Data schemeyesyesyesyes infoDynamic Fields enables on-the-fly addition of new fieldsschema-free
Typing infopredefined data types such as float or dateyesyesyesyes infosupports customizable data types and automatic typingyes
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.nononoyes
Secondary indexesyesyesyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLyesA subset of ANSI SQL is implemented infobut no views, foreign keys, triggersSQL-like DML and DDL statementsSolr Parallel SQL Interfaceno
APIs and other access methodsArrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC
JDBC
ODBC
JDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP/JSON API
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesC
C# info3rd party driver
C++
Crystal info3rd party driver
Go info3rd party driver
Java
Lisp info3rd party driver
Python
R
Ruby info3rd party driver
Rust
Swift
Zig info3rd party driver
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
C++
Java
JavaScript (Node.js)
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresnonouser defined functionsJava pluginsno
Triggersnonoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingShardingSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replicationSource-replica replicationyesselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonooptimistic lockingAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyesyes
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.yesnoyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlnorights management via user accountsAccess rights for users and roles on table levelyesCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
DuckDBJaguarDBKineticaSolrSqrrl
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