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DBMS > Alibaba Cloud MaxCompute vs. Brytlyt vs. Faircom EDGE vs. Kinetica vs. Spark SQL

System Properties Comparison Alibaba Cloud MaxCompute vs. Brytlyt vs. Faircom EDGE vs. Kinetica vs. Spark SQL

Editorial information provided by DB-Engines
NameAlibaba Cloud MaxCompute  Xexclude from comparisonBrytlyt  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonKinetica  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionMaxCompute (previously known as ODPS) is a general purpose, fully managed, multi-tenancy data processing platform for large-scale data warehousingScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsFully vectorized database across both GPUs and CPUsSpark SQL is a component on top of 'Spark Core' for structured data processing
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
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
Score0.29
Rank#288  Overall
#131  Relational DBMS
Score0.02
Rank#368  Overall
#54  Key-value stores
#156  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.alibabacloud.com/­product/­maxcomputebrytlyt.iowww.faircom.com/­products/­faircom-edgewww.kinetica.comspark.apache.org/­sql
Technical documentationwww.alibabacloud.com/­help/­en/­maxcomputedocs.brytlyt.iodocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmldocs.kinetica.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAlibabaBrytlytFairCom CorporationKineticaApache Software Foundation
Initial release20162016197920122014
Current release5.0, August 2023V3, October 20207.1, August 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercialcommercial infoRestricted, free version availablecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++ and CUDAANSI C, C++C, C++Scala
Server operating systemshostedLinux
OS X
Windows
Android
Linux infoARM, x86
Raspbian
Windows
LinuxLinux
OS X
Windows
Data schemeyesyesFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateyesyesyes, ANSI Standard SQL Typesyesyes
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.noyes infospecific XML-type available, but no XML query functionality.yesnono
Secondary indexesnoyesyesyesno
SQL infoSupport of SQLSQL-like query languageyesyes infoANSI SQL queriesSQL-like DML and DDL statementsSQL-like DML and DDL statements
APIs and other access methodsFluentd
Flume
MaxCompute Console
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Supported programming languagesJava.Net
C
C++
Delphi
Java
Perl
Python
Tcl
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C++
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions infoin Javauser defined functions infoin PL/pgSQLyes info.Net, JavaScript, C/C++user defined functionsno
Triggersnoyesyesyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceFile partitioning infoCustomizable business rules for partitioningShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceSource-replica replicationyes infoSynchronous and asynchronous realtime replication based on transaction logsSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Tunable Consistency
Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesyes infowhen using SQLyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoacross SQL and NoSQLyesyes
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.noyesyes infoGPU vRAM or System RAMno
User concepts infoAccess controlAccess rights for users and rolesfine grained access rights according to SQL-standardFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Access rights for users and roles on table levelno

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More resources
Alibaba Cloud MaxComputeBrytlytFaircom EDGE infoformerly c-treeEDGEKineticaSpark SQL
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