DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Apache IoTDB vs. Google Cloud Bigtable vs. Graph Engine vs. Microsoft Azure Data Explorer

System Properties Comparison Apache IoTDB vs. Google Cloud Bigtable vs. Graph Engine vs. Microsoft Azure Data Explorer

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineFully managed big data interactive analytics platform
Primary database modelTime Series DBMSKey-value store
Wide column store
Graph DBMS
Key-value 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
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websiteiotdb.apache.orgcloud.google.com/­bigtablewww.graphengine.ioazure.microsoft.com/­services/­data-explorer
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlcloud.google.com/­bigtable/­docswww.graphengine.io/­docs/­manualdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software FoundationGoogleMicrosoftMicrosoft
Initial release2018201520102019
Current release1.1.0, April 2023cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoMIT Licensecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava.NET and C
Server operating systemsAll OS with a Java VM (>= 1.8)hosted.NEThosted
Data schemeyesschema-freeyesFixed schema with schema-less datatypes (dynamic)
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-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.nononoyes
Secondary indexesyesnoall fields are automatically indexed
SQL infoSupport of SQLSQL-like query languagenonoKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBC
Native API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
RESTful HTTP APIMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
C#
C++
F#
Visual Basic
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyesnoyesYes, possible languages: KQL, Python, R
Triggersyesnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Shardinghorizontal partitioningSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasInternal 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 methodsIntegration with Hadoop and SparkyesSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
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 datanoAtomic single-row operationsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesno
User concepts infoAccess controlyesAccess 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
Apache IoTDBGoogle Cloud BigtableGraph Engine infoformer name: TrinityMicrosoft Azure Data Explorer
Recent citations in the news

TsFile: A Standard Format for IoT Time Series Data
27 February 2024, The New Stack

Linux 6.5 With AMD P-State EPP Default Brings Performance & Power Efficiency Benefits For Ryzen Servers
21 September 2023, Phoronix

AMD EPYC 8324P / 8324PN Siena 32-Core Siena Linux Server Performance Review
10 October 2023, Phoronix

Apache Promotes IoT Database Project
25 September 2020, Datanami

IoTDB Provides Data Management for Industrial Edge IT
15 October 2020, The New Stack

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

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

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

Google Cloud makes it cheaper to run smaller workloads on Bigtable
7 April 2020, TechCrunch

provided by Google News

Trinity
2 June 2023, Microsoft

Open source Microsoft Graph Engine takes on Neo4j
13 February 2017, InfoWorld

IBM releases Graph, a service that can outperform SQL databases
27 July 2016, GeekWire

Aerospike Is Now a Graph Database, Too
21 June 2023, Datanami

The graph analytics landscape 2019 - DataScienceCentral.com
27 February 2019, Data Science Central

provided by Google News

Public Preview: Azure Data Explorer connector for Apache Flink | Azure updates
8 January 2024, azure.microsoft.com

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

Azure Data Explorer: Log and telemetry analytics benchmark
16 August 2022, azure.microsoft.com

Introducing Microsoft Fabric: The data platform for the era of AI | Microsoft Azure Blog
23 May 2023, azure.microsoft.com

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

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

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.

RaimaDB logo

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

SingleStore logo

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

Present your product here