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DBMS > Fauna vs. IBM Db2 warehouse vs. Microsoft Azure Data Explorer vs. Splice Machine

System Properties Comparison Fauna vs. IBM Db2 warehouse vs. Microsoft Azure Data Explorer vs. Splice Machine

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Editorial information provided by DB-Engines
NameFauna infopreviously named FaunaDB  Xexclude from comparisonIBM Db2 warehouse infoformerly named IBM dashDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionFauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.Cloud-based data warehousing serviceFully managed big data interactive analytics platformOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument store
Graph DBMS
Relational DBMS
Time Series DBMS
Relational 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
Score1.52
Rank#153  Overall
#26  Document stores
#14  Graph DBMS
#71  Relational DBMS
#13  Time Series DBMS
Score1.30
Rank#164  Overall
#75  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitefauna.comwww.ibm.com/­products/­db2/­warehouseazure.microsoft.com/­services/­data-explorersplicemachine.com
Technical documentationdocs.fauna.comdocs.microsoft.com/­en-us/­azure/­data-explorersplicemachine.com/­how-it-works
DeveloperFauna, Inc.IBMMicrosoftSplice Machine
Initial release2014201420192014
Current releasecloud service with continuous releases3.1, March 2021
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaJava
Server operating systemshostedhostedhostedLinux
OS X
Solaris
Windows
Data schemeschema-freeyesFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or datenoyesyes 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.nono infoImport/export of XML data possibleyes
Secondary indexesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLnoyesKusto Query Language (KQL), SQL subsetyes
APIs and other access methodsRESTful HTTP API.NET Client API
JDBC
ODBC
OLE DB
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC#
Go
Java
JavaScript
Python
Ruby
Scala
Swift
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsPL/SQL, SQL PLYes, possible languages: KQL, Python, Ryes infoJava
Triggersnoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning infoconsistent hashingShardingSharding infoImplicit feature of the cloud serviceShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
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.noyesnoyes
User concepts infoAccess controlIdentity management, authentication, and access controlfine grained access rights according to SQL-standardAzure Active Directory AuthenticationAccess rights for users, groups and roles according to SQL-standard

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More resources
Fauna infopreviously named FaunaDBIBM Db2 warehouse infoformerly named IBM dashDBMicrosoft Azure Data ExplorerSplice Machine
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