DB-EnginesExtremeDB for everyone with an RTOSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Google Cloud Bigtable vs. Microsoft Azure Data Explorer vs. MonetDB vs. PieCloudDB vs. RRDtool

System Properties Comparison Google Cloud Bigtable vs. Microsoft Azure Data Explorer vs. MonetDB vs. PieCloudDB vs. RRDtool

Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMonetDB  Xexclude from comparisonPieCloudDB  Xexclude from comparisonRRDtool  Xexclude from comparison
DescriptionGoogle'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 platformA relational database management system that stores data in columnsA cloud-native analytic database platform with new technologoy for elastic MPPIndustry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database. infoThe data is stored in a circular buffer, thus the system storage footprint remains constant over time.
Primary database modelKey-value store
Wide column store
Relational DBMS infocolumn orientedRelational DBMSRelational DBMSTime Series 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
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score1.72
Rank#145  Overall
#67  Relational DBMS
Score0.25
Rank#304  Overall
#138  Relational DBMS
Score1.87
Rank#136  Overall
#11  Time Series DBMS
Websitecloud.google.com/­bigtableazure.microsoft.com/­services/­data-explorerwww.monetdb.orgwww.openpie.comoss.oetiker.ch/­rrdtool
Technical documentationcloud.google.com/­bigtable/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerwww.monetdb.org/­Documentationoss.oetiker.ch/­rrdtool/­doc
DeveloperGoogleMicrosoftMonetDB BVOpenPieTobias Oetiker
Initial release2015201920041999
Current releasecloud service with continuous releasesDec2023 (11.49), December 20232.1, January 20231.8.0, 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoMozilla Public License 2.0commercialOpen Source infoGPL V2 and FLOSS
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 languageCC infoImplementations in Java (e.g. RRD4J) and C# available
Server operating systemshostedhostedFreeBSD
Linux
OS X
Solaris
Windows
hostedHP-UX
Linux
Data schemeschema-freeFixed schema with schema-less datatypes (dynamic)yesyesyes
Typing infopredefined data types such as float or datenoyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyesNumeric data only
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.noyesno infoExporting into and restoring from XML files possible
Secondary indexesnoall fields are automatically indexedyesyesno
SQL infoSupport of SQLnoKusto Query Language (KQL), SQL subsetyes infoSQL 2003 with some extensionsyesno
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
CLI Client
JDBC
ODBC
in-process shared library
Pipes
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Java
PL/SQL
Python
R
C infowith librrd library
C# infowith a different implementation of RRDTool
Java infowith a different implementation of RRDTool
JavaScript (Node.js) infowith a different implementation of RRDTool
Lua
Perl
PHP infowith a wrapper library
Python
Ruby
Server-side scripts infoStored proceduresnoYes, possible languages: KQL, Python, Ryes, in SQL, C, Ruser defined functionsno
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceSharding via remote tablesyesnone
Replication methods infoMethods for redundantly storing data on multiple nodesInternal 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.none infoSource-replica replication available in experimental statusyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency
Immediate Consistency
Immediate Consistencynone
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes infoby using the rrdcached daemon
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
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Azure Active Directory Authenticationfine grained access rights according to SQL-standardUser Roles and pluggable authentication with full SQL Standardno
More information provided by the system vendor
Google Cloud BigtableMicrosoft Azure Data ExplorerMonetDBPieCloudDBRRDtool
Specific characteristicsPieCloudDB, OpenPie's flagship product, is a cutting-edge cloud-native data warehouse....
» more
Competitive advantagesExtreme Elastic: PieCloudDB utilizes a cutting-edge eMPP cloud-native architecture...
» more
Typical application scenariosPieCloudDB is ideal for Data mining applications that require extreme scalability...
» more
Key customersSail-Cloud China Shipbuilding Group Haizhou System Soochow Securities ​etc.,
» more
Licensing and pricing modelsPieCloudDB Community Edition: Community License, Free Download, Self-Hosted Deployment;...
» more

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
Google Cloud BigtableMicrosoft Azure Data ExplorerMonetDBPieCloudDBRRDtool
DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

show all

Recent citations in the 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 Cloud makes it cheaper to run smaller workloads on Bigtable
7 April 2020, TechCrunch

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

Microsoft Introduces Azure Integration Environments and Business Process Tracking in Public Preview
23 November 2023, InfoQ.com

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

provided by Google News

In 2024 the MonetDB Foundation was established for the preservation, maintenance and further development of the ...
31 January 2024, Centrum Wiskunde & Informatica (CWI)

MonetDB Secures Investment From (and Partners With) ServiceNow
9 December 2021, Datanami

PostgreSQL, MonetDB, and Too-Big-for-Memory Data in R - Part I - DataScienceCentral.com
6 April 2018, Data Science Central

How MonetDB Exploits Modern CPU Performance | by Dwi Prasetyo Adi Nugroho
14 January 2020, Towards Data Science

Monet DB The Column-Store Pioneer - open source for you
4 September 2019, Open Source For You

provided by Google News

Critical IP spoofing bug patched in Cacti
15 December 2022, The Daily Swig

SQLi vulnerability in Cacti could lead to RCE (CVE-2023-51448)
9 January 2024, Help Net Security

How to install Cacti SNMP Monitor on Ubuntu
24 November 2017, TechRepublic

Installation Guide for Collectd and Collectd-Web to Monitor Server Resources in Linux
29 November 2017, Linux.com

SNMP: The Little Protocol That Could
7 November 2020, Techopedia

provided by Google News



Share this page

Featured Products

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

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

Neo4j logo

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

Milvus logo

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

SingleStore logo

The database to transact, analyze and contextualize your data in real time.
Try it today.

Present your product here