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DBMS > Alibaba Cloud MaxCompute vs. CrateDB vs. Hive vs. Microsoft Azure Data Explorer vs. VelocityDB

System Properties Comparison Alibaba Cloud MaxCompute vs. CrateDB vs. Hive vs. Microsoft Azure Data Explorer vs. VelocityDB

Editorial information provided by DB-Engines
NameAlibaba Cloud MaxCompute  Xexclude from comparisonCrateDB  Xexclude from comparisonHive  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonVelocityDB  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 Lucenedata warehouse software for querying and managing large distributed datasets, built on HadoopFully managed big data interactive analytics platformA .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)
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
Relational DBMSRelational DBMS infocolumn orientedGraph DBMS
Object oriented DBMS
Secondary database modelsRelational DBMSDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.77
Rank#214  Overall
#98  Relational DBMS
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.05
Rank#358  Overall
#36  Graph DBMS
#16  Object oriented DBMS
Websitewww.alibabacloud.com/­product/­maxcomputecratedb.comhive.apache.orgazure.microsoft.com/­services/­data-explorervelocitydb.com
Technical documentationwww.alibabacloud.com/­help/­en/­maxcomputecratedb.com/­docscwiki.apache.org/­confluence/­display/­Hive/­Homedocs.microsoft.com/­en-us/­azure/­data-explorervelocitydb.com/­UserGuide
DeveloperAlibabaCrateApache Software Foundation infoinitially developed by FacebookMicrosoftVelocityDB Inc
Initial release20162013201220192011
Current release3.1.3, April 2022cloud service with continuous releases7.x
License infoCommercial or Open SourcecommercialOpen SourceOpen Source infoApache Version 2commercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
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#
Server operating systemshostedAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportAll OS with a Java VMhostedAny that supports .NET
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes
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.nonoyesno
Secondary indexesnoyesyesall fields are automatically indexedyes
SQL infoSupport of SQLSQL-like query languageyes, but no triggers and constraints, and PostgreSQL compatibilitySQL-like DML and DDL statementsKusto Query Language (KQL), SQL subsetno
APIs and other access methodsFluentd
Flume
MaxCompute Console
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
JDBC
ODBC
Thrift
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
.Net
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++
Java
PHP
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
Server-side scripts infoStored proceduresuser defined functions infoin Javauser defined functions (Javascript)yes infouser defined functions and integration of map-reduceYes, possible languages: KQL, Python, Rno
Triggersnononoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyCallbacks are triggered when data changes
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceShardingShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceConfigurable replication on table/partition-levelselectable replication factoryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyes infoquery execution via MapReduceSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Read-after-write consistency on record level
Eventual ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononono
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 strategynonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
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 for users and rolesrights management via user accountsAccess rights for users, groups and rolesAzure Active Directory AuthenticationBased on Windows Authentication
More information provided by the system vendor
Alibaba Cloud MaxComputeCrateDBHiveMicrosoft Azure Data ExplorerVelocityDB
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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Alibaba Cloud MaxComputeCrateDBHiveMicrosoft Azure Data ExplorerVelocityDB
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