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 > eXtremeDB vs. FatDB vs. Microsoft Azure Data Explorer vs. Spark SQL vs. YugabyteDB

System Properties Comparison eXtremeDB vs. FatDB vs. Microsoft Azure Data Explorer vs. Spark SQL vs. YugabyteDB

Editorial information provided by DB-Engines
NameeXtremeDB  Xexclude from comparisonFatDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSpark SQL  Xexclude from comparisonYugabyteDB  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionNatively in-memory DBMS with options for persistency, high-availability and clusteringA .NET NoSQL DBMS that can integrate with and extend SQL Server.Fully managed big data interactive analytics platformSpark SQL is a component on top of 'Spark Core' for structured data processingHigh-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL.
Primary database modelRelational DBMS
Time Series DBMS
Document store
Key-value store
Relational DBMS infocolumn orientedRelational DBMSRelational 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
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.74
Rank#223  Overall
#103  Relational DBMS
#18  Time Series DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score2.91
Rank#102  Overall
#51  Relational DBMS
Websitewww.mcobject.comazure.microsoft.com/­services/­data-explorerspark.apache.org/­sqlwww.yugabyte.com
Technical documentationwww.mcobject.com/­docs/­extremedb.htmdocs.microsoft.com/­en-us/­azure/­data-explorerspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.yugabyte.com
github.com/­yugabyte/­yugabyte-db
DeveloperMcObjectFatCloudMicrosoftApache Software FoundationYugabyte Inc.
Initial release20012012201920142017
Current release8.2, 2021cloud service with continuous releases3.5.0 ( 2.13), September 20232.19, September 2023
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
YugabyteDB Managed is the fully managed database-as-a-service offering of YugabyteDB. Get started quickly, and effortlessly ensure continuous availability and limitless scale of your cloud native applications.
Implementation languageC and C++C#ScalaC and C++
Server operating systemsAIX
HP-UX
Linux
macOS
Solaris
Windows
WindowshostedLinux
OS X
Windows
Linux
OS X
Data schemeyesschema-freeFixed schema with schema-less datatypes (dynamic)yesdepending on used data model
Typing infopredefined data types such as float or dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyes
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.no infosupport of XML interfaces availableyesnono
Secondary indexesyesyesall fields are automatically indexednoyes
SQL infoSupport of SQLyes infowith the option: eXtremeSQLno infoVia inetgration in SQL ServerKusto Query Language (KQL), SQL subsetSQL-like DML and DDL statementsyes, PostgreSQL compatible
APIs and other access methods.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
JDBC
YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language
YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL
Supported programming languages.Net
C
C#
C++
Java
Lua
Python
Scala
C#.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Java
Python
R
Scala
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
Scala
Server-side scripts infoStored proceduresyesyes infovia applicationsYes, possible languages: KQL, Python, Rnoyes infosql, plpgsql, C
Triggersyes infoby defining eventsyes infovia applicationsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning / shardingShardingSharding infoImplicit feature of the cloud serviceyes, utilizing Spark CoreHash and Range Sharding, row-level geo-partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesActive Replication Fabricâ„¢ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
selectable replication factoryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.noneBased on Raft distributed consensus protocol, minimum 3 replicas for continuous availability
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Strong consistency on writes and tunable consistency on reads
Foreign keys infoReferential integrityyesnononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnononoDistributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture.
Concurrency infoSupport for concurrent manipulation of datayes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infobased on RocksDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonono
User concepts infoAccess controlno infoCan implement custom security layer via applicationsAzure Active Directory Authenticationnoyes
More information provided by the system vendor
eXtremeDBFatDBMicrosoft Azure Data ExplorerSpark SQLYugabyteDB
Specific characteristicseXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
» more
YugabyteDB is an open source distributed SQL database for cloud native transactional...
» more
Competitive advantageseXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
» more
PostgreSQL compatible: Get instantly productive with a PostgreSQL compatible RDBMS....
» more
Typical application scenariosIoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» more
Systems of record and engagement for cloud native applications that require resilience,...
» more
Key customersSchneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more
Market metricsWith hundreds of customers and over 30 million devices/applications using the product...
» more
2 Million+ lifetime clusters deployed, 6.5K+ GitHub stars, 7K YugabyteDB Community...
» more
Licensing and pricing modelsFor server use cases, there is a simple per-server license irrespective of the number...
» more
Apache 2.0 license for the database
» 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
eXtremeDBFatDBMicrosoft Azure Data ExplorerSpark SQLYugabyteDB
Recent citations in the news

Latest embedded DBMS supports asymmetric multiprocessing systems
24 May 2023, Embedded

McObject Announces the Release of eXtremeDB/rt 1.2
23 May 2023, Embedded Computing Design

The Data in Hard Real-time SCADA Systems Lets Companies Do More with Less
11 August 2023, Automation.com

McObject & IBM Set New Records for Speed & Stability in STAC-M3 Benchmark for Capital Markets
3 November 2015, Yahoo Lifestyle UK

McObject Delivers eXtremeDB 8.4 Improving Performance, Security, and Developer Productivity
13 May 2024, Embedded Computing Design

provided by Google News

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

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

Controlling costs in Azure Data Explorer using down-sampling and aggregation
11 February 2019, azure.microsoft.com

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, azure.microsoft.com

provided by Google News

Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services
18 October 2023, AWS Blog

What is Apache Spark? The big data platform that crushed Hadoop
3 April 2024, InfoWorld

Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2024
1 April 2024, Simplilearn

Performant IPv4 Range Spark Joins | by Jean-Claude Cote
24 January 2024, Towards Data Science

18 Top Big Data Tools and Technologies to Know About in 2024
24 January 2024, TechTarget

provided by Google News

YugabyteDB Becomes First Distributed SQL Database Vendor to Complete CIS Benchmark
1 February 2024, Datanami

YugabyteDB 2.21 Introduces Industry's First Native Disaster Recovery Orchestration Solution for a Distributed SQL ...
30 April 2024, Business Wire

The surprising link between Formula One and enterprise PostgreSQL optimisation
28 March 2024, The Stack

Yugabyte Achieves PCI DSS Level 1 Compliance, Validating Secure and Scalable Distributed PostgreSQL for ...
14 March 2024, Business Wire

Can Yugabyte Become The Defacto Database For Large-Scale, Cloud Native Applications?
19 May 2022, Forbes

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

SingleStore logo

Database for your real-time AI and Analytics Apps.
Try it today.

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.

Present your product here