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 Druid vs. Microsoft Azure Data Explorer vs. OpenMLDB vs. SwayDB vs. Tarantool

System Properties Comparison Apache Druid vs. Microsoft Azure Data Explorer vs. OpenMLDB vs. SwayDB vs. Tarantool

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOpenMLDB  Xexclude from comparisonSwayDB  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataFully managed big data interactive analytics platformAn open-source machine learning database that provides a feature platform for training and inferenceAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storageIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMS infocolumn orientedTime Series DBMSKey-value storeDocument store
Key-value store
Relational 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
Relational DBMSSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.10
Rank#359  Overall
#36  Time Series DBMS
Score0.04
Rank#387  Overall
#61  Key-value stores
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Websitedruid.apache.orgazure.microsoft.com/­services/­data-exploreropenmldb.aiswaydb.simer.auwww.tarantool.io
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.microsoft.com/­en-us/­azure/­data-exploreropenmldb.ai/­docs/­zh/­mainwww.tarantool.io/­en/­doc
DeveloperApache Software Foundation and contributorsMicrosoft4 Paradigm Inc.Simer PlahaVK
Initial release20122019202020182008
Current release29.0.1, April 2024cloud service with continuous releases2024-2 February 20242.10.0, May 2022
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen SourceOpen Source infoGNU Affero GPL V3.0Open Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++, Java, ScalaScalaC and C++
Server operating systemsLinux
OS X
Unix
hostedLinuxBSD
Linux
macOS
Data schemeyes infoschema-less columns are supportedFixed schema with schema-less datatypes (dynamic)Fixed schemaschema-freeFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesnostring, double, decimal, uuid, integer, blob, boolean, datetime
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.noyesnonono
Secondary indexesyesall fields are automatically indexedyesnoyes
SQL infoSupport of SQLSQL for queryingKusto Query Language (KQL), SQL subsetyesnoFull-featured ANSI SQL support
APIs and other access methodsJDBC
RESTful HTTP/JSON API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
SQLAlchemy
Open binary protocol
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C++
Go
Java
Python
Scala
Java
Kotlin
Scala
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresnoYes, possible languages: KQL, Python, RnonoLua, C and SQL stored procedures
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynonoyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedSharding infoImplicit feature of the cloud servicehorizontal partitioningnoneSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationnoneAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate ConsistencyCasual consistency across sharding partitions
Eventual consistency within replicaset partition infowhen using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition infowhen using Raft
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoAtomic execution of operationsACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, cooperative multitasking
Durability infoSupport for making data persistentyesyesyesyesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyesyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAzure Active Directory Authenticationfine grained access rights according to SQL-standardnoAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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 DruidMicrosoft Azure Data ExplorerOpenMLDBSwayDBTarantool
DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
9 November 2021,  Vladimir Perepelytsya, Tarantool (sponsor) 

show all

Recent citations in the news

Apache Druid Wins Best Big Data Product in the 2023 BigDATAwire Readers' Choice Awards
26 January 2024, Datanami

'Lucifer' Botnet Turns Up the Heat on Apache Hadoop Servers
21 February 2024, Dark Reading

New DDoS malware Attacking Apache big-data stack, Hadoop, & Druid Servers
26 February 2024, GBHackers

Apache Druid Takes Its Place In The Pantheon Of Databases
16 June 2022, The Next Platform

How to connect DataGrip to Apache Druid | by Zisis Flokas
18 October 2021, Towards Data Science

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, azure.microsoft.com

Update records in a Kusto Database (public preview) | Azure updates
20 February 2024, azure.microsoft.com

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

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

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

provided by Google News

MLOp practice: using OpenMLDB in the real-time anti-fraud model for the bank's online transaction
23 August 2021, Towards Data Science

Predictive maintenance — 5minutes demo of an end to end machine learning project
13 August 2021, Towards Data Science

Compared to Native Spark 3.0, We Have Achieved Significant Optimization Effects in the AI
3 August 2021, Towards Data Science

provided by Google News

Deploying Tarantool Cartridge applications with zero effort (Part 1)
16 December 2019, Хабр

VShard — horizontal scaling in Tarantool
7 March 2019, Хабр

Accelerating PHP connectors for Tarantool using Async, Swoole, and Parallel
18 December 2019, Хабр

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.

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

Present your product here