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. EJDB vs. Firebolt vs. Microsoft Azure Data Explorer vs. mSQL

System Properties Comparison Apache IoTDB vs. EJDB vs. Firebolt vs. Microsoft Azure Data Explorer vs. mSQL

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonEJDB  Xexclude from comparisonFirebolt  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonmSQL infoMini SQL  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 FlinkEmbeddable document-store database library with JSON representation of queries (in MongoDB style)Highly scalable cloud data warehouse and analytics product infoForked from ClickhouseFully managed big data interactive analytics platformmSQL (Mini SQL) is a simple and lightweight RDBMS
Primary database modelTime Series DBMSDocument storeRelational DBMSRelational 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
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.31
Rank#296  Overall
#44  Document stores
Score1.73
Rank#140  Overall
#63  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score1.27
Rank#169  Overall
#76  Relational DBMS
Websiteiotdb.apache.orggithub.com/­Softmotions/­ejdbwww.firebolt.ioazure.microsoft.com/­services/­data-explorerhughestech.com.au/­products/­msql
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mddocs.firebolt.iodocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software FoundationSoftmotionsFirebolt Analytics Inc.MicrosoftHughes Technologies
Initial release20182012202020191994
Current release1.1.0, April 2023cloud service with continuous releases4.4, October 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoGPLv2commercialcommercialcommercial infofree licenses can be provided
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaCC
Server operating systemsAll OS with a Java VM (>= 1.8)server-lesshostedhostedAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeyesschema-freeyesFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyes infostring, integer, double, bool, date, object_idyesyes 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.noyesno
Secondary indexesyesnoyesall fields are automatically indexedyes
SQL infoSupport of SQLSQL-like query languagenoyesKusto Query Language (KQL), SQL subsetA subset of ANSI SQL is implemented infono subqueries, aggregate functions, views, foreign keys, triggers
APIs and other access methodsJDBC
Native API
in-process shared library.Net
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
Go
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Delphi
Java
Perl
PHP
Tcl
Server-side scripts infoStored proceduresyesnonoYes, possible languages: KQL, Python, Rno
Triggersyesnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)noneSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasnonedepending on storage layeryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparknoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual Consistency
Immediate Consistency
none
Foreign keys infoReferential integritynono infotypically not needed, however similar functionality with collection joins possiblenono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononono
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/Write Lockingyesno
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.yesnono
User concepts infoAccess controlyesnoAzure Active Directory Authenticationno

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 IoTDBEJDBFireboltMicrosoft Azure Data ExplorermSQL infoMini SQL
Recent citations in the news

AMD EPYC 4364P & 4564P @ DDR5-4800 / DDR5-5200 vs. Intel Xeon E-2488 Review
6 June 2024, Phoronix

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

Apache Promotes IoT Database Project
25 September 2020, Datanami

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

provided by Google News

10 Best Data Pipeline Tools of 2024 to Boost Your Productivity
20 February 2024, Datamation

Cloud data unicorn Firebolt fires dozens of employees
7 September 2022, CTech

Firebolt, a data warehouse startup, raises $100M at a $1.4B valuation for faster, cheaper analytics on large data sets
26 January 2022, TechCrunch

Firebolt vs Snowflake | Data Warehousing Platform Comparison
1 April 2022, TechRepublic

Firebolt, Israeli Cloud Data Warehouse Startup Forklifts Forward
5 January 2021, Forbes

provided by Google News

We’re retiring Azure Time Series Insights on 7 July 2024 – transition to Azure Data Explorer | Azure updates
31 May 2024, Microsoft

Update records in a Kusto Database (public preview) | Azure updates
20 February 2024, Microsoft

Public Preview: Azure Data Explorer connector for Apache Flink | Azure updates
8 January 2024, Microsoft

Announcing General Availability to migrate Virtual Network injected Azure Data Explorer Cluster to Private Endpoints ...
5 February 2024, Microsoft

New Features for graph-match KQL Operator: Enhanced Pattern Matching and Cycle Control | Azure updates
24 January 2024, Microsoft

provided by Google News

Higher Education PS rules out ghost students before PAC
29 November 2018, diggers.news

provided by Google News



Share this page

Featured Products

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

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