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DBMS > Alibaba Cloud MaxCompute vs. Badger vs. Brytlyt vs. Google Cloud Datastore vs. Spark SQL

System Properties Comparison Alibaba Cloud MaxCompute vs. Badger vs. Brytlyt vs. Google Cloud Datastore vs. Spark SQL

Editorial information provided by DB-Engines
NameAlibaba Cloud MaxCompute  Xexclude from comparisonBadger  Xexclude from comparisonBrytlyt  Xexclude from comparisonGoogle Cloud Datastore  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 warehousingAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformSpark 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 tablesKey-value storeRelational DBMSDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.77
Rank#214  Overall
#98  Relational DBMS
Score0.14
Rank#331  Overall
#49  Key-value stores
Score0.29
Rank#288  Overall
#131  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.alibabacloud.com/­product/­maxcomputegithub.com/­dgraph-io/­badgerbrytlyt.iocloud.google.com/­datastorespark.apache.org/­sql
Technical documentationwww.alibabacloud.com/­help/­en/­maxcomputegodoc.org/­github.com/­dgraph-io/­badgerdocs.brytlyt.iocloud.google.com/­datastore/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAlibabaDGraph LabsBrytlytGoogleApache Software Foundation
Initial release20162017201620082014
Current release5.0, August 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC, C++ and CUDAScala
Server operating systemshostedBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
hostedLinux
OS X
Windows
Data schemeyesschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesnoyesyes, details hereyes
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 infospecific XML-type available, but no XML query functionality.nono
Secondary indexesnonoyesyesno
SQL infoSupport of SQLSQL-like query languagenoyesSQL-like query language (GQL)SQL-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
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languagesJavaGo.Net
C
C++
Delphi
Java
Perl
Python
Tcl
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions infoin Javanouser defined functions infoin PL/pgSQLusing Google App Engineno
TriggersnonoyesCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud servicenoneShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud servicenoneSource-replica replicationMulti-source replication using Paxosnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonoyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneImmediate 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.
Foreign keys infoReferential integritynonoyesyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.nononono
User concepts infoAccess controlAccess rights for users and rolesnofine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no

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More resources
Alibaba Cloud MaxComputeBadgerBrytlytGoogle Cloud DatastoreSpark SQL
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