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DBMS > Alibaba Cloud MaxCompute vs. Atos Standard Common Repository vs. CrateDB vs. Google Cloud Datastore

System Properties Comparison Alibaba Cloud MaxCompute vs. Atos Standard Common Repository vs. CrateDB vs. Google Cloud Datastore

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Editorial information provided by DB-Engines
NameAlibaba Cloud MaxCompute  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonCrateDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionMaxCompute (previously known as ODPS) is a general purpose, fully managed, multi-tenancy data processing platform for large-scale data warehousingHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksDistributed Database based on LuceneAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform
Primary database modelRelational DBMS infoa graph-processing framework is available with the graphs being stored in tablesDocument store
Key-value store
Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Document store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.84
Rank#209  Overall
#98  Relational DBMS
Score0.71
Rank#227  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#10  Vector DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Websitewww.alibabacloud.com/­product/­maxcomputeatos.net/en/convergence-creators/portfolio/standard-common-repositorycratedb.comcloud.google.com/­datastore
Technical documentationwww.alibabacloud.com/­help/­en/­maxcomputecratedb.com/­docscloud.google.com/­datastore/­docs
DeveloperAlibabaAtos Convergence CreatorsCrateGoogle
Initial release2016201620132008
Current release1703
License infoCommercial or Open SourcecommercialcommercialOpen Sourcecommercial
Cloud-based only infoOnly available as a cloud serviceyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava
Server operating systemshostedLinuxAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supporthosted
Data schemeyesSchema and schema-less with LDAP viewsFlexible Schema (defined schema, partial schema, schema free)schema-free
Typing infopredefined data types such as float or dateyesoptionalyesyes, details here
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.noyesnono
Secondary indexesnoyesyesyes
SQL infoSupport of SQLSQL-like query languagenoyes, but no triggers and constraints, and PostgreSQL compatibilitySQL-like query language (GQL)
APIs and other access methodsFluentd
Flume
MaxCompute Console
LDAPADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Supported programming languagesJavaAll languages with LDAP bindings.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions infoin Javanouser defined functions (Javascript)using Google App Engine
TriggersnoyesnoCallbacks using the Google Apps Engine
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceSharding infocell divisionShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceyesConfigurable replication on table/partition-levelMulti-source replication using Paxos
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Read-after-write consistency on record level
Immediate 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 integritynononoyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsno infounique row identifiers can be used for implementing an optimistic concurrency control strategyACID infoSerializable Isolation within Transactions, Read Committed outside of Transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono
User concepts infoAccess controlAccess rights for users and rolesLDAP bind authenticationrights management via user accountsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
Alibaba Cloud MaxComputeAtos Standard Common RepositoryCrateDBGoogle Cloud Datastore
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