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DBMS > Alibaba Cloud MaxCompute vs. Google Cloud Spanner vs. Kinetica vs. Microsoft Azure Data Explorer vs. RavenDB

System Properties Comparison Alibaba Cloud MaxCompute vs. Google Cloud Spanner vs. Kinetica vs. Microsoft Azure Data Explorer vs. RavenDB

Editorial information provided by DB-Engines
NameAlibaba Cloud MaxCompute  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRavenDB  Xexclude from comparison
DescriptionMaxCompute (previously known as ODPS) is a general purpose, fully managed, multi-tenancy data processing platform for large-scale data warehousingA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.Fully vectorized database across both GPUs and CPUsFully managed big data interactive analytics platformOpen Source Operational and Transactional Enterprise NoSQL Document Database
Primary database modelRelational DBMS infoa graph-processing framework is available with the graphs being stored in tablesRelational DBMSRelational DBMSRelational DBMS infocolumn orientedDocument store
Secondary database modelsSpatial DBMS
Time Series DBMS
Document store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.84
Rank#209  Overall
#98  Relational DBMS
Score2.84
Rank#100  Overall
#51  Relational DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score2.84
Rank#101  Overall
#18  Document stores
Websitewww.alibabacloud.com/­product/­maxcomputecloud.google.com/­spannerwww.kinetica.comazure.microsoft.com/­services/­data-explorerravendb.net
Technical documentationwww.alibabacloud.com/­help/­en/­maxcomputecloud.google.com/­spanner/­docsdocs.kinetica.comdocs.microsoft.com/­en-us/­azure/­data-explorerravendb.net/­docs
DeveloperAlibabaGoogleKineticaMicrosoftHibernating Rhinos
Initial release20162017201220192010
Current release7.1, August 2021cloud service with continuous releases5.4, July 2022
License infoCommercial or Open SourcecommercialcommercialcommercialcommercialOpen Source infoAGPL version 3, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++C#
Server operating systemshostedhostedLinuxhostedLinux
macOS
Raspberry Pi
Windows
Data schemeyesyesyesFixed schema with schema-less datatypes (dynamic)schema-free
Typing infopredefined data types such as float or dateyesyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesno
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.nononoyes
Secondary indexesnoyesyesall fields are automatically indexedyes
SQL infoSupport of SQLSQL-like query languageyes infoQuery statements complying to ANSI 2011SQL-like DML and DDL statementsKusto Query Language (KQL), SQL subsetSQL-like query language (RQL)
APIs and other access methodsFluentd
Flume
MaxCompute Console
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
Supported programming languagesJavaGo
Java
JavaScript (Node.js)
Python
C++
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions infoin Javanouser defined functionsYes, possible languages: KQL, Python, Ryes
Triggersnonoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceShardingShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceMulti-source replication with 3 replicas for regional instances.Source-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infousing Google Cloud DataflownoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
Foreign keys infoReferential integritynoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoStrict serializable isolationnonoACID, Cluster-wide transaction available
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.nonoyes infoGPU vRAM or System RAMno
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles on table levelAzure Active Directory AuthenticationAuthorization levels configured per client per database

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More resources
Alibaba Cloud MaxComputeGoogle Cloud SpannerKineticaMicrosoft Azure Data ExplorerRavenDB
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