DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Amazon CloudSearch vs. GeoMesa vs. LeanXcale vs. Vitess

System Properties Comparison Amazon CloudSearch vs. GeoMesa vs. LeanXcale vs. Vitess

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameAmazon CloudSearch  Xexclude from comparisonGeoMesa  Xexclude from comparisonLeanXcale  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionA hosted search engine service by Amazon with the data stored in Amazons cloudGeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelSearch engineSpatial DBMSKey-value store
Relational DBMS
Relational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.81
Rank#137  Overall
#12  Search engines
Score0.86
Rank#205  Overall
#4  Spatial DBMS
Score0.36
Rank#280  Overall
#40  Key-value stores
#129  Relational DBMS
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websiteaws.amazon.com/­cloudsearchwww.geomesa.orgwww.leanxcale.comvitess.io
Technical documentationdocs.aws.amazon.com/­cloudsearchwww.geomesa.org/­documentation/­stable/­user/­index.htmlvitess.io/­docs
DeveloperAmazonCCRi and othersLeanXcaleThe Linux Foundation, PlanetScale
Initial release2012201420152013
Current release5.0.0, May 202415.0.2, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache License 2.0commercialOpen Source infoApache Version 2.0, commercial licenses available
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 languageScalaGo
Server operating systemshostedDocker
Linux
macOS
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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.no
Secondary indexesyes infoall search fields are automatically indexedyesyes
SQL infoSupport of SQLnonoyes infothrough Apache Derbyyes infowith proprietary extensions
APIs and other access methodsHTTP APIJDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesC
Java
Scala
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnonoyes infoproprietary syntax
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesyes infoautomatic partitioning across Amazon Search Instance as requireddepending on storage layerSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infomanaged transparently by AWSdepending on storage layerMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemdepending on storage layerImmediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynonoyesyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
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.depending on storage layeryesyes
User concepts infoAccess controlauthentication via encrypted signaturesyes infodepending on the DBMS used for storageUsers with fine-grained authorization concept infono user groups or roles

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 CloudSearchGeoMesaLeanXcaleVitess
DB-Engines blog posts

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

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

show all

Spatial database management systems
6 April 2021, Matthias Gelbmann

show all

Recent citations in the news

Amazon CloudSearch – Start Searching in One Hour for Less Than $100 / Month | Amazon Web Services
12 April 2012, AWS Blog

Searching CloudTrail Logs Easily with Amazon CloudSearch | AWS Startups Blog
21 October 2014, AWS Blog

AWS, Microsoft and Google should retire these cloud services
2 June 2020, TechTarget

CloudSearch Update – Price Reduction, Hebrew & Japanese Support, Partitioning, CloudTrail | Amazon Web Services
19 November 2014, AWS Blog

AI-Powered Data Discovery with Amazon Kendra and AWS Glue Data Catalog
16 July 2021, Towards Data Science

provided by Google News

PlanetScale Unveils Distributed MySQL Database Service Based on Vitess
18 May 2021, Datanami

PlanetScale grabs YouTube-developed open-source tech, promises Vitess DBaaS with on-the-fly schema changes
18 May 2021, The Register

They scaled YouTube -- now they’ll shard everyone with PlanetScale
13 December 2018, TechCrunch

With Vitess 4.0, database vendor matures cloud-native platform
13 November 2019, TechTarget

Massively Scaling MySQL Using Vitess
19 February 2019, InfoQ.com

provided by Google News



Share this page

Featured Products

Milvus logo

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

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.

Present your product here