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DBMS > Alibaba Cloud MaxCompute vs. Kinetica vs. RDF4J vs. Snowflake vs. Splice Machine

System Properties Comparison Alibaba Cloud MaxCompute vs. Kinetica vs. RDF4J vs. Snowflake vs. Splice Machine

Editorial information provided by DB-Engines
NameAlibaba Cloud MaxCompute  Xexclude from comparisonKinetica  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSnowflake  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionMaxCompute (previously known as ODPS) is a general purpose, fully managed, multi-tenancy data processing platform for large-scale data warehousingFully vectorized database across both GPUs and CPUsRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Cloud-based data warehousing service for structured and semi-structured dataOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMS infoa graph-processing framework is available with the graphs being stored in tablesRelational DBMSRDF storeRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.77
Rank#214  Overall
#98  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Score121.33
Rank#9  Overall
#6  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.alibabacloud.com/­product/­maxcomputewww.kinetica.comrdf4j.orgwww.snowflake.comsplicemachine.com
Technical documentationwww.alibabacloud.com/­help/­en/­maxcomputedocs.kinetica.comrdf4j.org/­documentationdocs.snowflake.net/­manuals/­index.htmlsplicemachine.com/­how-it-works
DeveloperAlibabaKineticaSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Snowflake Computing Inc.Splice Machine
Initial release20162012200420142014
Current release7.1, August 20213.1, March 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.commercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++JavaJava
Server operating systemshostedLinuxLinux
OS X
Unix
Windows
hostedLinux
OS X
Solaris
Windows
Data schemeyesyesyes infoRDF Schemasyes infosupport of semi-structured data formats (JSON, XML, Avro)yes
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.nonoyes
Secondary indexesnoyesyesyes
SQL infoSupport of SQLSQL-like query languageSQL-like DML and DDL statementsnoyesyes
APIs and other access methodsFluentd
Flume
MaxCompute Console
JDBC
ODBC
RESTful HTTP API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
CLI Client
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
Supported programming languagesJavaC++
Java
JavaScript (Node.js)
Python
Java
PHP
Python
JavaScript (Node.js)
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions infoin Javauser defined functionsyesuser defined functionsyes infoJava
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyesno infosimilar concept for controling cloud resourcesyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceShardingnoneyesShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceSource-replica replicationnoneyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infoIsolation support depends on the API usedACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes infoin-memory storage is supported as wellyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoGPU vRAM or System RAMnoyes
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users and roles on table levelnoUsers with fine-grained authorization concept, user roles and pluggable authenticationAccess rights for users, groups and roles according to SQL-standard

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More resources
Alibaba Cloud MaxComputeKineticaRDF4J infoformerly known as SesameSnowflakeSplice Machine
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