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DBMS > Amazon CloudSearch vs. MemSQL vs. Vertica

System Properties Comparison Amazon CloudSearch vs. MemSQL vs. Vertica

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Editorial information provided by DB-Engines
NameAmazon CloudSearch  Xexclude from comparisonMemSQL  Xexclude from comparisonVertica infoVertica Analytics Platform  Xexclude from comparison
DescriptionA hosted search engine service by Amazon with the data stored in Amazons cloudMySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storageColumnar relational DBMS designed to handle modern analytic workloads, enabling fast query performance
Primary database modelSearch engineRelational DBMSRelational DBMS
Secondary database modelsDocument storeDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.06
Rank#86  Overall
#9  Search engines
Score4.52
Rank#70  Overall
#37  Relational DBMS
Score22.65
Rank#29  Overall
#17  Relational DBMS
Websiteaws.amazon.com/­cloudsearchwww.memsql.comwww.vertica.com
Technical documentationdocs.aws.amazon.com/­cloudsearchdocs.memsql.comwww.vertica.com/­documentation/­vertica
DeveloperAmazonMemSQL Inc.Vertica / Micro Focus infoprior to that Hewlett Packard
Initial release201220132005
Current release6.8, August 2019Vertica Analytics Platform 9.2.x, March 2019
License infoCommercial or Open Sourcecommercialcommercial infofree developer edition availablecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud serviceyesnono infoavailable on Amazon AWS and Microsoft Azure
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++
Server operating systemshostedLinux info64 bit version requiredLinux
Data schemeyesyesyes infoUnstructured data can be stored in specific Flex-Tables
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.noyes
Secondary indexesyes infoall search fields are automatically indexedyesno infoThe concept of 'projections' can be used instead of indexes.
SQL infoSupport of SQLnoyes, but no triggers and foreign keysyes infonearly full SQL99 without support for indexes and triggers
APIs and other access methodsHTTP APIJDBC
ODBC
ADO.NET
JDBC
Kafka
ODBC
Proprietary protocol
RESTful HTTP API
Supported programming languagesBash
C
C#
Java
JavaScript (Node.js)
Python
C++
Java
Perl
Python
R
Server-side scripts infoStored proceduresnoyesyes
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesyes infoautomatic partitioning across Amazon Search Instance as requiredShardingSharding infoSegmentation, Projection Segmentation, Hash Segmentation
Replication methods infoMethods for redundantly storing data on multiple nodesyes infomanaged transparently by AWSMaster-slave replicationMaster-master replication infoCluster level and Object level replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infowith Vertica Connector for Hadoop
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency only within each nodeImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoOnly isolation level: READ COMMITEDACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes
User concepts infoAccess controlauthentication via encrypted signaturesfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Amazon CloudSearchMemSQLVertica infoVertica Analytics Platform
Specific characteristicsColumnar storage, MPP, Hybrid storage model, Aggressive data compression, High availability,...
» more
Competitive advantagesPerformance at exabyte scale, Deploy anywhere, Open source innovation, Analysis in...
» more
Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are available
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Amazon CloudSearchMemSQLVertica infoVertica Analytics Platform
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Recent citations in the news

Amazon CloudSearch: Just What You Were Looking For?
11 September 2016, Wired News

Is Amazon CloudSearch superior to do-it-yourself search tools?
24 January 2014, TechTarget

Use Amazon CloudSearch to build search indexes
25 July 2014, TechTarget

Enterprise Semantic Search Software Market Size Growth Forecast 2020 to 2025
15 January 2020, News by aeresearch

Enterprise Search Software Market 2020 Share, Size, Future
23 January 2020, openPR

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5 December 2019, Business Wire

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25 September 2019, Blocks and Files

10 Predictions for Big Data in 2020
3 January 2020, Database Trends and Applications

MemSQL Ups Ante on Cloud Databases
24 September 2019, Datanami

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24 January 2020, TDWI

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1 April 2019, Datanami

Micro Focus Announces Vertica in Eon Mode for Pure Storage
18 September 2019, DevOps.com

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26 November 2019, IT Brief Australia

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