DB-EnginesExtremeDB: mitigate connectivity issues in a DBMSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Blueflood vs. FatDB vs. Google Cloud Bigtable vs. Microsoft Azure Data Explorer

System Properties Comparison Blueflood vs. FatDB vs. Google Cloud Bigtable vs. Microsoft Azure Data Explorer

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameBlueflood  Xexclude from comparisonFatDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionScalable TimeSeries DBMS based on CassandraA .NET NoSQL DBMS that can integrate with and extend SQL Server.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Fully managed big data interactive analytics platform
Primary database modelTime Series DBMSDocument store
Key-value store
Key-value store
Wide column store
Relational DBMS infocolumn oriented
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
Score0.13
Rank#346  Overall
#33  Time Series DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websiteblueflood.iocloud.google.com/­bigtableazure.microsoft.com/­services/­data-explorer
Technical documentationgithub.com/­rax-maas/­blueflood/­wikicloud.google.com/­bigtable/­docsdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperRackspaceFatCloudGoogleMicrosoft
Initial release2013201220152019
Current releasecloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC#
Server operating systemsLinux
OS X
Windowshostedhosted
Data schemepredefined schemeschema-freeschema-freeFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyesnoyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
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
Secondary indexesnoyesnoall fields are automatically indexed
SQL infoSupport of SQLnono infoVia inetgration in SQL ServernoKusto Query Language (KQL), SQL subset
APIs and other access methodsHTTP REST.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC#C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnoyes infovia applicationsnoYes, possible languages: KQL, Python, R
Triggersnoyes infovia applicationsnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on Cassandraselectable replication factorInternal replication in Colossus, and regional replication between two clusters in different zonesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency
Immediate Consistency
Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoAtomic single-row operationsno
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.nonono
User concepts infoAccess controlnono infoCan implement custom security layer via applicationsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Azure Active Directory Authentication

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
BluefloodFatDBGoogle Cloud BigtableMicrosoft Azure Data Explorer
Recent citations in the news

Real-Time Performance and Health Monitoring Using Netdata
2 September 2019, CNX Software

provided by Google News

Google's AI-First Strategy Brings Vector Support To Cloud Databases
1 March 2024, Forbes

Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs
31 January 2022, InfoQ.com

Google scales up Cloud Bigtable NoSQL database
27 January 2022, TechTarget

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

Google introduces Cloud Bigtable managed NoSQL database to process data at scale
6 May 2015, VentureBeat

provided by Google News

Azure Data Explorer: Log and telemetry analytics benchmark
16 August 2022, Microsoft

Controlling costs in Azure Data Explorer using down-sampling and aggregation
11 February 2019, Microsoft

Providing modern data transfer and storage service at Microsoft with Microsoft Azure - Inside Track Blog
13 July 2023, Microsoft

Individually great, collectively unmatched: Announcing updates to 3 great Azure Data Services
7 February 2019, Microsoft

Log and Telemetry Analytics Performance Benchmark
16 August 2022, Gigaom

provided by Google News



Share this page

Featured Products

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Present your product here