DB-EnginesExtremeDB for everyone with an RTOSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Amazon Aurora vs. Kinetica vs. Solr vs. YottaDB

System Properties Comparison Amazon Aurora vs. Kinetica vs. Solr vs. YottaDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonKinetica  Xexclude from comparisonSolr  Xexclude from comparisonYottaDB  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonFully vectorized database across both GPUs and CPUsA widely used distributed, scalable search engine based on Apache LuceneA fast and solid embedded Key-value store
Primary database modelRelational DBMSRelational DBMSSearch engineKey-value store
Secondary database modelsDocument storeSpatial DBMS
Time Series DBMS
Spatial DBMSRelational DBMS infousing the Octo plugin
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.57
Rank#51  Overall
#32  Relational DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Score0.28
Rank#306  Overall
#44  Key-value stores
Websiteaws.amazon.com/­rds/­aurorawww.kinetica.comsolr.apache.orgyottadb.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmldocs.kinetica.comsolr.apache.org/­resources.htmlyottadb.com/­resources/­documentation
DeveloperAmazonKineticaApache Software FoundationYottaDB, LLC
Initial release2015201220062001
Current release7.1, August 20219.6.1, May 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2Open Source infoAGPL 3.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++JavaC
Server operating systemshostedLinuxAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Docker
Linux
Data schemeyesyesyes infoDynamic Fields enables on-the-fly addition of new fieldsschema-free
Typing infopredefined data types such as float or dateyesyesyes infosupports customizable data types and automatic typingno
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.yesnoyesno
Secondary indexesyesyesyes infoAll search fields are automatically indexedno
SQL infoSupport of SQLyesSQL-like DML and DDL statementsSolr Parallel SQL Interfaceby using the Octo plugin
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP/JSON API
PostgreSQL wire protocol infousing the Octo plugin
Proprietary protocol
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
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
C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust
Server-side scripts infoStored proceduresyesuser defined functionsJava plugins
Triggersyesyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replicationyesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Foreign keys infoReferential integrityyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnooptimistic lockingoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.yesyes infoGPU vRAM or System RAMyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users and roles on table levelyesUsers and groups based on OS-security mechanisms

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Amazon AuroraKineticaSolrYottaDB
DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

The popularity of cloud-based DBMSs has increased tenfold in four years
7 February 2017, Matthias Gelbmann

Amazon - the rising star in the DBMS market
3 August 2015, Matthias Gelbmann

show all

Elasticsearch replaced Solr as the most popular search engine
12 January 2016, Paul Andlinger

Enterprise Search Engines almost double their popularity in the last 12 months
2 July 2014, Paul Andlinger

The DB-Engines ranking includes now search engines
4 February 2013, Paul Andlinger

show all

Recent citations in the news

Build a FedRAMP compliant generative AI-powered chatbot using Amazon Aurora Machine Learning and Amazon ...
10 June 2024, AWS Blog

Introducing the Advanced Python Wrapper Driver for Amazon Aurora | Amazon Web Services
11 June 2024, AWS Blog

Join the preview of Amazon Aurora Limitless Database | Amazon Web Services
27 November 2023, AWS Blog

Improve the performance of generative AI workloads on Amazon Aurora with Optimized Reads and pgvector | Amazon ...
9 February 2024, AWS Blog

Continuously replicate Amazon DynamoDB changes to Amazon Aurora PostgreSQL using AWS Lambda | Amazon ...
14 May 2024, AWS Blog

provided by Google News

Kinetica Elevates RAG with Fast Access to Real-Time Data
26 March 2024, Datanami

Kinetica ramps up RAG for generative AI, empowering enterprises with real-time operational data
18 March 2024, SiliconANGLE News

Kinetica Launches Generative AI Solution for Real-Time Inferencing Powered by NVIDIA AI Enterprise
18 March 2024, GlobeNewswire

Transforming spatiotemporal data analysis with GPUs and generative AI
30 October 2023, InfoWorld

Kinetica Delivers Real-Time Vector Similarity Search
22 March 2024, Geospatial World

provided by Google News

SOLR-led walkout demands better conditions for Compass workers
27 February 2024, Daily Northwestern

Solr Network Launches Groundbreaking Solana Token Creator
28 May 2024, AccessWire

(SOLR) Proactive Strategies
27 May 2024, news.stocktradersdaily.com

Have Insiders Been Buying Solar Alliance Energy Inc. (CVE:SOLR) Shares?
27 May 2024, Yahoo Movies UK

SOLR hosts teach-in of labor movements at Northwestern
28 January 2024, Daily Northwestern

provided by Google News



Share this page

Featured Products

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Present your product here