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DBMS > Alibaba Cloud Table Store vs. CrateDB vs. EsgynDB vs. Hazelcast

System Properties Comparison Alibaba Cloud Table Store vs. CrateDB vs. EsgynDB vs. Hazelcast

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Editorial information provided by DB-Engines
NameAlibaba Cloud Table Store  Xexclude from comparisonCrateDB  Xexclude from comparisonEsgynDB  Xexclude from comparisonHazelcast  Xexclude from comparison
DescriptionA fully managed Wide Column Store for large quantities of semi-structured data with real-time accessDistributed Database based on LuceneEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionA widely adopted in-memory data grid
Primary database modelWide column storeDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSKey-value store
Secondary database modelsRelational DBMSDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.26
Rank#301  Overall
#12  Wide column stores
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Websitewww.alibabacloud.com/­product/­table-storecratedb.comwww.esgyn.cnhazelcast.com
Technical documentationwww.alibabacloud.com/­help/­en/­tablestorecratedb.com/­docshazelcast.org/­imdg/­docs
DeveloperAlibabaCrateEsgynHazelcast
Initial release2016201320152008
Current release5.3.6, November 2023
License infoCommercial or Open SourcecommercialOpen SourcecommercialOpen Source infoApache Version 2; 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.
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 languageJavaC++, JavaJava
Server operating systemshostedAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinuxAll OS with a Java VM
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)yesschema-free
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.nononoyes infothe object must implement a serialization strategy
Secondary indexesnoyesyesyes
SQL infoSupport of SQLnoyes, but no triggers and constraints, and PostgreSQL compatibilityyesSQL-like query language
APIs and other access methodsHTTP APIADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
ADO.NET
JDBC
ODBC
JCache
JPA
Memcached protocol
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
All languages supporting JDBC/ODBC/ADO.Net.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresnouser defined functions (Javascript)Java Stored Proceduresyes infoEvent Listeners, Executor Services
Triggersnononoyes infoEvents
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceConfigurable replication on table/partition-levelMulti-source replication between multi datacentersyes infoReplicated Map
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Read-after-write consistency on record level
Immediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithm
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 strategyACIDone or two-phase-commit; repeatable reads; read commited
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 accountsfine grained access rights according to SQL-standardRole-based access control
More information provided by the system vendor
Alibaba Cloud Table StoreCrateDBEsgynDBHazelcast
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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Alibaba Cloud Table StoreCrateDBEsgynDBHazelcast
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