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DBMS > Alibaba Cloud MaxCompute vs. Google Cloud Bigtable vs. IBM Db2 Event Store vs. Microsoft Azure Data Explorer vs. Spark SQL

System Properties Comparison Alibaba Cloud MaxCompute vs. Google Cloud Bigtable vs. IBM Db2 Event Store vs. Microsoft Azure Data Explorer vs. Spark SQL

Editorial information provided by DB-Engines
NameAlibaba Cloud MaxCompute  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonMicrosoft Azure Data Explorer  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 warehousingGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Distributed Event Store optimized for Internet of Things use casesFully managed big data interactive analytics 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 store
Wide column store
Event Store
Time Series DBMS
Relational DBMS infocolumn orientedRelational DBMS
Secondary database modelsDocument 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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.84
Rank#209  Overall
#98  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score0.27
Rank#309  Overall
#2  Event Stores
#28  Time Series DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.alibabacloud.com/­product/­maxcomputecloud.google.com/­bigtablewww.ibm.com/­products/­db2-event-storeazure.microsoft.com/­services/­data-explorerspark.apache.org/­sql
Technical documentationwww.alibabacloud.com/­help/­en/­maxcomputecloud.google.com/­bigtable/­docswww.ibm.com/­docs/­en/­db2-event-storedocs.microsoft.com/­en-us/­azure/­data-explorerspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAlibabaGoogleIBMMicrosoftApache Software Foundation
Initial release20162015201720192014
Current release2.0cloud service with continuous releases3.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercialcommercial infofree developer edition availablecommercialOpen Source infoApache 2.0
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 and C++Scala
Server operating systemshostedhostedLinux infoLinux, macOS, Windows for the developer additionhostedLinux
OS X
Windows
Data schemeyesschema-freeyesFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesnoyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes
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.nononoyesno
Secondary indexesnononoall fields are automatically indexedno
SQL infoSupport of SQLSQL-like query languagenoyes infothrough the embedded Spark runtimeKusto Query Language (KQL), SQL subsetSQL-like DML and DDL statements
APIs and other access methodsFluentd
Flume
MaxCompute Console
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
Supported programming languagesJavaC#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions infoin JavanoyesYes, possible languages: KQL, Python, Rno
Triggersnononoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceShardingShardingSharding infoImplicit feature of the cloud serviceyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceInternal replication in Colossus, and regional replication between two clusters in different zonesActive-active shard replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsnonono
Concurrency infoSupport for concurrent manipulation of datayesyesNo - written data is immutableyesyes
Durability infoSupport for making data persistentyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesnono
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardAzure Active Directory Authenticationno

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More resources
Alibaba Cloud MaxComputeGoogle Cloud BigtableIBM Db2 Event StoreMicrosoft Azure Data ExplorerSpark SQL
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