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DBMS > Alibaba Cloud MaxCompute vs. Amazon DynamoDB vs. Graph Engine vs. HEAVY.AI vs. Kinetica

System Properties Comparison Alibaba Cloud MaxCompute vs. Amazon DynamoDB vs. Graph Engine vs. HEAVY.AI vs. Kinetica

Editorial information provided by DB-Engines
NameAlibaba Cloud MaxCompute  Xexclude from comparisonAmazon DynamoDB  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonKinetica  Xexclude from comparison
DescriptionMaxCompute (previously known as ODPS) is a general purpose, fully managed, multi-tenancy data processing platform for large-scale data warehousingHosted, scalable database service by Amazon with the data stored in Amazons cloudA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareFully vectorized database across both GPUs and CPUs
Primary database modelRelational DBMS infoa graph-processing framework is available with the graphs being stored in tablesDocument store
Key-value store
Graph DBMS
Key-value store
Relational DBMSRelational DBMS
Secondary database modelsSpatial DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.85
Rank#203  Overall
#96  Relational DBMS
Score70.06
Rank#17  Overall
#3  Document stores
#2  Key-value stores
Score0.56
Rank#241  Overall
#21  Graph DBMS
#34  Key-value stores
Score1.41
Rank#153  Overall
#71  Relational DBMS
Score0.42
Rank#261  Overall
#120  Relational DBMS
Websitewww.alibabacloud.com/­product/­maxcomputeaws.amazon.com/­dynamodbwww.graphengine.iogithub.com/­heavyai/­heavydb
www.heavy.ai
www.kinetica.com
Technical documentationwww.alibabacloud.com/­help/­en/­maxcomputedocs.aws.amazon.com/­dynamodbwww.graphengine.io/­docs/­manualdocs.heavy.aidocs.kinetica.com
DeveloperAlibabaAmazonMicrosoftHEAVY.AI, Inc.Kinetica
Initial release20162012201020162012
Current release5.10, January 20227.1, August 2021
License infoCommercial or Open Sourcecommercialcommercial infofree tier for a limited amount of database operationsOpen Source infoMIT LicenseOpen Source infoApache Version 2; enterprise edition availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation language.NET and CC++ and CUDAC, C++
Server operating systemshostedhosted.NETLinuxLinux
Data schemeyesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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 indexesnoyesnoyes
SQL infoSupport of SQLSQL-like query languagenonoyesSQL-like DML and DDL statements
APIs and other access methodsFluentd
Flume
MaxCompute Console
RESTful HTTP APIRESTful HTTP APIJDBC
ODBC
Thrift
Vega
JDBC
ODBC
RESTful HTTP API
Supported programming languagesJava.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby
C#
C++
F#
Visual Basic
All languages supporting JDBC/ODBC/Thrift
Python
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functions infoin Javanoyesnouser defined functions
Triggersnoyes infoby integration with AWS Lambdanonoyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceShardinghorizontal partitioningSharding infoRound robinSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceyesMulti-source replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency infocan be specified for read operations
Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoACID across one or more tables within a single AWS account and regionnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)fine grained access rights according to SQL-standardAccess rights for users and roles on table level

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More resources
Alibaba Cloud MaxComputeAmazon DynamoDBGraph Engine infoformer name: TrinityHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Kinetica
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