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DBMS > Alibaba Cloud Table Store vs. CrateDB vs. Snowflake vs. Solr

System Properties Comparison Alibaba Cloud Table Store vs. CrateDB vs. Snowflake vs. Solr

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Editorial information provided by DB-Engines
NameAlibaba Cloud Table Store  Xexclude from comparisonCrateDB  Xexclude from comparisonSnowflake  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionA fully managed Wide Column Store for large quantities of semi-structured data with real-time accessDistributed Database based on LuceneCloud-based data warehousing service for structured and semi-structured dataA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelWide column storeDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSSearch engine
Secondary database modelsRelational DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.31
Rank#297  Overall
#11  Wide column stores
Score0.71
Rank#227  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#10  Vector DBMS
Score130.36
Rank#8  Overall
#5  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Websitewww.alibabacloud.com/­product/­table-storecratedb.comwww.snowflake.comsolr.apache.org
Technical documentationwww.alibabacloud.com/­help/­en/­tablestorecratedb.com/­docsdocs.snowflake.net/­manuals/­index.htmlsolr.apache.org/­resources.html
DeveloperAlibabaCrateSnowflake Computing Inc.Apache Software Foundation
Initial release2016201320142006
Current release9.6.1, May 2024
License infoCommercial or Open SourcecommercialOpen SourcecommercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.
Implementation languageJavaJava
Server operating systemshostedAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supporthostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)yes infosupport of semi-structured data formats (JSON, XML, Avro)yes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyesyes infosupports customizable data types and automatic typing
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.nonoyesyes
Secondary indexesnoyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLnoyes, but no triggers and constraints, and PostgreSQL compatibilityyesSolr Parallel SQL Interface
APIs and other access methodsHTTP APIADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
CLI Client
JDBC
ODBC
Java API
RESTful HTTP/JSON API
Supported programming languagesJava
Python
.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
JavaScript (Node.js)
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnouser defined functions (Javascript)user defined functionsJava plugins
Triggersnonono infosimilar concept for controling cloud resourcesyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceShardingyesSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceConfigurable replication on table/partition-levelyesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Read-after-write consistency on record level
Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsno infounique row identifiers can be used for implementing an optimistic concurrency control strategyACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.nononoyes
User concepts infoAccess controlAccess rights based on subaccounts and tokensrights management via user accountsUsers with fine-grained authorization concept, user roles and pluggable authenticationyes
More information provided by the system vendor
Alibaba Cloud Table StoreCrateDBSnowflakeSolr
Specific characteristicsThe enterprise database for time series, documents, and vectors. Distributed - Native...
» more
Competitive advantagesResponse time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more
Typical application scenarios​ IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more
Key customersAcross all continents, CrateDB is used by companies of all sizes to meet the most...
» more
Market metricsThe CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more
Licensing and pricing modelsSee CrateDB pricing >
» more

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More resources
Alibaba Cloud Table StoreCrateDBSnowflakeSolr
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