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DBMS > Alibaba Cloud MaxCompute vs. Google Cloud Datastore vs. Kinetica vs. RDF4J vs. Splice Machine

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

Editorial information provided by DB-Engines
NameAlibaba Cloud MaxCompute  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonKinetica  Xexclude from comparisonRDF4J infoformerly known as Sesame  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 warehousingAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformFully vectorized database across both GPUs and CPUsRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Open-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 tablesDocument storeRelational DBMSRDF storeRelational 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
Score4.47
Rank#76  Overall
#12  Document stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.alibabacloud.com/­product/­maxcomputecloud.google.com/­datastorewww.kinetica.comrdf4j.orgsplicemachine.com
Technical documentationwww.alibabacloud.com/­help/­en/­maxcomputecloud.google.com/­datastore/­docsdocs.kinetica.comrdf4j.org/­documentationsplicemachine.com/­how-it-works
DeveloperAlibabaGoogleKineticaSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Splice Machine
Initial release20162008201220042014
Current release7.1, August 20213.1, March 2021
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++JavaJava
Server operating systemshostedhostedLinuxLinux
OS X
Unix
Windows
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeyesyes infoRDF Schemasyes
Typing infopredefined data types such as float or dateyesyes, details hereyesyesyes
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.nonono
Secondary indexesnoyesyesyesyes
SQL infoSupport of SQLSQL-like query languageSQL-like query language (GQL)SQL-like DML and DDL statementsnoyes
APIs and other access methodsFluentd
Flume
MaxCompute Console
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
JDBC
Native Spark Datasource
ODBC
Supported programming languagesJava.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
Java
PHP
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions infoin Javausing Google App Engineuser defined functionsyesyes infoJava
TriggersnoCallbacks using the Google Apps Engineyes infotriggers when inserted values for one or more columns fall within a specified rangeyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceShardingShardingnoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceMulti-source replication using PaxosSource-replica replicationnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infousing Google Cloud DataflownonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID infoIsolation support depends on the API usedACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes infoin-memory storage is supported as wellyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles on table levelnoAccess rights for users, groups and roles according to SQL-standard

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More resources
Alibaba Cloud MaxComputeGoogle Cloud DatastoreKineticaRDF4J infoformerly known as SesameSplice Machine
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