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DBMS > Alibaba Cloud Table Store vs. Solr vs. Vertica

System Properties Comparison Alibaba Cloud Table Store vs. Solr vs. Vertica

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Editorial information provided by DB-Engines
NameAlibaba Cloud Table Store  Xexclude from comparisonSolr  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionA fully managed Wide Column Store for large quantities of semi-structured data with real-time accessA widely used distributed, scalable search engine based on Apache LuceneCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelWide column storeSearch engineRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.26
Rank#301  Overall
#12  Wide column stores
Score42.91
Rank#24  Overall
#3  Search engines
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitewww.alibabacloud.com/­product/­table-storesolr.apache.orgwww.vertica.com
Technical documentationwww.alibabacloud.com/­help/­en/­tablestoresolr.apache.org/­resources.htmlvertica.com/­documentation
DeveloperAlibabaApache Software FoundationOpenText infopreviously Micro Focus and Hewlett Packard
Initial release201620062005
Current release9.5.0, February 202412.0.3, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud serviceyesnono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++
Server operating systemshostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
Data schemeschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyesyes 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.noyesno
Secondary indexesnoyes infoAll search fields are automatically indexedNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnoSolr Parallel SQL InterfaceFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsHTTP APIJava API
RESTful HTTP/JSON API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesJava
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnoJava pluginsyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyes infoUser configurable commands triggered on index changesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceyesMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsoptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.noyesno
User concepts infoAccess controlAccess rights based on subaccounts and tokensyesfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Alibaba Cloud Table StoreSolrVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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More resources
Alibaba Cloud Table StoreSolrVertica infoOpenText™ Vertica™
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