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DBMS > Alibaba Cloud MaxCompute vs. Amazon Redshift vs. GridGain vs. Spark SQL vs. Splice Machine

System Properties Comparison Alibaba Cloud MaxCompute vs. Amazon Redshift vs. GridGain vs. Spark SQL vs. Splice Machine

Editorial information provided by DB-Engines
NameAlibaba Cloud MaxCompute  Xexclude from comparisonAmazon Redshift  Xexclude from comparisonGridGain  Xexclude from comparisonSpark SQL  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 warehousingLarge scale data warehouse service for use with business intelligence toolsGridGain is an in-memory computing platform, built on Apache IgniteSpark SQL is a component on top of 'Spark Core' for structured data processingOpen-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 DBMSKey-value store
Relational DBMS
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.84
Rank#209  Overall
#98  Relational DBMS
Score16.88
Rank#35  Overall
#22  Relational DBMS
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitewww.alibabacloud.com/­product/­maxcomputeaws.amazon.com/­redshiftwww.gridgain.comspark.apache.org/­sqlsplicemachine.com
Technical documentationwww.alibabacloud.com/­help/­en/­maxcomputedocs.aws.amazon.com/­redshiftwww.gridgain.com/­docs/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsplicemachine.com/­how-it-works
DeveloperAlibabaAmazon (based on PostgreSQL)GridGain Systems, Inc.Apache Software FoundationSplice Machine
Initial release20162012200720142014
Current releaseGridGain 8.5.13.5.0 ( 2.13), September 20233.1, March 2021
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache 2.0Open Source infoAGPL 3.0, commercial license available
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 languageCJava, C++, .NetScalaJava
Server operating systemshostedhostedLinux
OS X
Solaris
Windows
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemeyesyesyesyesyes
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.nonoyesno
Secondary indexesnorestrictedyesnoyes
SQL infoSupport of SQLSQL-like query languageyes infodoes not fully support an SQL-standardANSI-99 for query and DML statements, subset of DDLSQL-like DML and DDL statementsyes
APIs and other access methodsFluentd
Flume
MaxCompute Console
JDBC
ODBC
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
Supported programming languagesJavaAll languages supporting JDBC/ODBCC#
C++
Java
PHP
Python
Ruby
Scala
Java
Python
R
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions infoin Javauser defined functions infoin Pythonyes (compute grid and cache interceptors can be used instead)noyes infoJava
Triggersnonoyes (cache interceptors and events)noyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceShardingShardingyes, utilizing Spark CoreShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceyesyes (replicated cache)noneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyes (compute grid and hadoop accelerator)Yes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infoinformational only, not enforced by the systemnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
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.noyesyesnoyes
User concepts infoAccess controlAccess rights for users and rolesfine grained access rights according to SQL-standardSecurity Hooks for custom implementationsnoAccess rights for users, groups and roles according to SQL-standard

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More resources
Alibaba Cloud MaxComputeAmazon RedshiftGridGainSpark SQLSplice Machine
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