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DBMS > Alibaba Cloud PolarDB vs. BigObject vs. CrateDB vs. Kyligence Enterprise

System Properties Comparison Alibaba Cloud PolarDB vs. BigObject vs. CrateDB vs. Kyligence Enterprise

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Editorial information provided by DB-Engines
NameAlibaba Cloud PolarDB  Xexclude from comparisonBigObject  Xexclude from comparisonCrateDB  Xexclude from comparisonKyligence Enterprise  Xexclude from comparison
DescriptionA cloud-native relational database compatible with MySQL, PostgreSQL, and Oracle. Designed for business critical applications.Analytic DBMS for real-time computations and queriesDistributed Database based on LuceneA distributed analytics engine for big data, built on top of Apache Kylin
Primary database modelRelational DBMSRelational DBMS infoa hierachical model (tree) can be imposedDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.59
Rank#241  Overall
#110  Relational DBMS
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score0.40
Rank#269  Overall
#124  Relational DBMS
Websitewww.alibabacloud.com/­product/­polardbbigobject.iocratedb.comkyligence.io/­kyligence-enterprise
Technical documentationwww.alibabacloud.com/­help/­en/­polardb/­product-overviewdocs.bigobject.iocratedb.com/­docs
DeveloperAlibabaBigObject, Inc.CrateKyligence, Inc.
Initial release201520132016
License infoCommercial or Open Sourcecommercialcommercial infofree community edition availableOpen Sourcecommercial
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.
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 systemshostedLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinux
Data schemeyesyesFlexible Schema (defined schema, partial schema, schema free)yes
Typing infopredefined data types such as float or dateyesyesyesyes
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.yesnonono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsyes, but no triggers and constraints, and PostgreSQL compatibilityANSI SQL for queries (using Apache Calcite)
APIs and other access methodsJDBC
ODBC
fluentd
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
JDBC
ODBC
RESTful HTTP 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
Server-side scripts infoStored proceduresyesLuauser defined functions (Javascript)
Triggersyesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud servicenoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud servicenoneConfigurable replication on table/partition-level
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneEventual Consistency
Read-after-write consistency on record level
Immediate Consistency
Foreign keys infoReferential integrityyesyes infoautomatically between fact table and dimension tablesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono infounique row identifiers can be used for implementing an optimistic concurrency control strategy
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/write lock on objects (tables, trees)yesyes
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.yesyesnono
User concepts infoAccess controlfine grained access rights according to SQL-standardnorights management via user accounts
More information provided by the system vendor
Alibaba Cloud PolarDBBigObjectCrateDBKyligence Enterprise
Specific characteristicsPolarDB, previously ApsaraDB for PolarDB, is a cloud-native relational database designed...
» more
The enterprise database for time series, documents, and vectors. Distributed - Native...
» more
Competitive advantagesWebinar: Top Scientists Live: Tech Secrets to Double 11's Success Revealed. White...
» more
Response time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more
Typical application scenariosCreating a Robust Cloud-Based Database for Fintech, E-Commerce and Gaming. Learn...
» more
​ 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 modelsSpecification and pricing. You can use either of the following billing methods to...
» more
See CrateDB pricing >
» more

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More resources
Alibaba Cloud PolarDBBigObjectCrateDBKyligence Enterprise
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