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DBMS > Alibaba Cloud MaxCompute vs. CrateDB vs. Heroic vs. Linter

System Properties Comparison Alibaba Cloud MaxCompute vs. CrateDB vs. Heroic vs. Linter

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Editorial information provided by DB-Engines
NameAlibaba Cloud MaxCompute  Xexclude from comparisonCrateDB  Xexclude from comparisonHeroic  Xexclude from comparisonLinter  Xexclude from comparison
DescriptionMaxCompute (previously known as ODPS) is a general purpose, fully managed, multi-tenancy data processing platform for large-scale data warehousingDistributed Database based on LuceneTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchRDBMS for high security requirements
Primary database modelRelational DBMS infoa graph-processing framework is available with the graphs being stored in tablesDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Time Series DBMSRelational DBMS
Secondary database modelsRelational DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.78
Rank#221  Overall
#102  Relational DBMS
Score0.73
Rank#229  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score0.57
Rank#250  Overall
#21  Time Series DBMS
Score0.10
Rank#350  Overall
#153  Relational DBMS
Websitewww.alibabacloud.com/­product/­maxcomputecratedb.comgithub.com/­spotify/­heroiclinter.ru
Technical documentationwww.alibabacloud.com/­help/­en/­maxcomputecratedb.com/­docsspotify.github.io/­heroic
DeveloperAlibabaCrateSpotifyrelex.ru
Initial release2016201320141990
License infoCommercial or Open SourcecommercialOpen SourceOpen Source infoApache 2.0commercial
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 languageJavaJavaC and C++
Server operating systemshostedAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-freeyes
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.nononono
Secondary indexesnoyesyes infovia Elasticsearchyes
SQL infoSupport of SQLSQL-like query languageyes, but no triggers and constraints, and PostgreSQL compatibilitynoyes
APIs and other access methodsFluentd
Flume
MaxCompute Console
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
HQL (Heroic Query Language, a JSON-based language)
HTTP API
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
Supported programming languagesJava.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
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
Server-side scripts infoStored proceduresuser defined functions infoin Javauser defined functions (Javascript)noyes infoproprietary syntax with the possibility to convert from PL/SQL
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceConfigurable replication on table/partition-levelyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Read-after-write consistency on record level
Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infounique row identifiers can be used for implementing an optimistic concurrency control strategynoACID
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.nonono
User concepts infoAccess controlAccess rights for users and rolesrights management via user accountsfine grained access rights according to SQL-standard
More information provided by the system vendor
Alibaba Cloud MaxComputeCrateDBHeroicLinter
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 MaxComputeCrateDBHeroicLinter
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