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DBMS > Alibaba Cloud MaxCompute vs. Google BigQuery vs. Microsoft Azure Cosmos DB vs. Sphinx vs. WakandaDB

System Properties Comparison Alibaba Cloud MaxCompute vs. Google BigQuery vs. Microsoft Azure Cosmos DB vs. Sphinx vs. WakandaDB

Editorial information provided by DB-Engines
NameAlibaba Cloud MaxCompute  Xexclude from comparisonGoogle BigQuery  Xexclude from comparisonMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB  Xexclude from comparisonSphinx  Xexclude from comparisonWakandaDB  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 with append-only tablesGlobally distributed, horizontally scalable, multi-model database serviceOpen source search engine for searching in data from different sources, e.g. relational databasesWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelRelational DBMS infoa graph-processing framework is available with the graphs being stored in tablesRelational DBMSDocument store
Graph DBMS
Key-value store
Wide column store
Search engineObject oriented DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.84
Rank#209  Overall
#98  Relational DBMS
Score58.10
Rank#19  Overall
#13  Relational DBMS
Score27.71
Rank#27  Overall
#4  Document stores
#2  Graph DBMS
#3  Key-value stores
#3  Wide column stores
Score5.95
Rank#55  Overall
#5  Search engines
Score0.10
Rank#356  Overall
#16  Object oriented DBMS
Websitewww.alibabacloud.com/­product/­maxcomputecloud.google.com/­bigqueryazure.microsoft.com/­services/­cosmos-dbsphinxsearch.comwakanda.github.io
Technical documentationwww.alibabacloud.com/­help/­en/­maxcomputecloud.google.com/­bigquery/­docslearn.microsoft.com/­azure/­cosmos-dbsphinxsearch.com/­docswakanda.github.io/­doc
DeveloperAlibabaGoogleMicrosoftSphinx Technologies Inc.Wakanda SAS
Initial release20162010201420012012
Current release3.5.1, February 20232.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud serviceyesyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++, JavaScript
Server operating systemshostedhostedhostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeyesyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyes infoJSON typesnoyes
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 indexesnonoyes infoAll properties auto-indexed by defaultyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query languageyesSQL-like query languageSQL-like query language (SphinxQL)no
APIs and other access methodsFluentd
Flume
MaxCompute Console
RESTful HTTP/JSON APIDocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API
Proprietary protocolRESTful HTTP API
Supported programming languagesJava.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
JavaScript
Server-side scripts infoStored proceduresuser defined functions infoin Javauser defined functions infoin JavaScriptJavaScriptnoyes
TriggersnonoJavaScriptnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud servicenoneSharding infoImplicit feature of the cloud serviceSharding infoPartitioning is done manually, search queries against distributed index is supportednone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceyes infoImplicit feature of the cloud servicenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnowith Hadoop integration infoIntegration with Hadoop/HDInsight on Azure*nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyBounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency infoConsistency level configurable on request level
Session Consistency
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infoSince BigQuery is designed for querying dataMulti-item ACID transactions with snapshot isolation within a partitionnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlAccess rights for users and rolesAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)Access rights can be defined down to the item levelnoyes

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More resources
Alibaba Cloud MaxComputeGoogle BigQueryMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBSphinxWakandaDB
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