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DBMS > Databricks vs. Faircom EDGE vs. Fauna vs. Microsoft Azure Data Explorer vs. TerminusDB

System Properties Comparison Databricks vs. Faircom EDGE vs. Fauna vs. Microsoft Azure Data Explorer vs. TerminusDB

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonFauna infopreviously named FaunaDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTerminusDB infoformer name was DataChemist  Xexclude from comparison
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsFauna 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.Fully managed big data interactive analytics platformScalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships
Primary database modelDocument store
Relational DBMS
Key-value store
Relational DBMS
Document store
Graph DBMS
Relational DBMS
Time Series DBMS
Relational DBMS infocolumn orientedGraph 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
RDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.09
Rank#362  Overall
#53  Key-value stores
#155  Relational DBMS
Score1.55
Rank#151  Overall
#26  Document stores
#14  Graph DBMS
#71  Relational DBMS
#13  Time Series DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.23
Rank#316  Overall
#27  Graph DBMS
Websitewww.databricks.comwww.faircom.com/­products/­faircom-edgefauna.comazure.microsoft.com/­services/­data-explorerterminusdb.com
Technical documentationdocs.databricks.comdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmldocs.fauna.comdocs.microsoft.com/­en-us/­azure/­data-explorerterminusdb.github.io/­terminusdb/­#
DeveloperDatabricksFairCom CorporationFauna, Inc.MicrosoftDataChemist Ltd.
Initial release20131979201420192018
Current releaseV3, October 2020cloud service with continuous releases11.0.0, January 2023
License infoCommercial or Open Sourcecommercialcommercial infoRestricted, free version availablecommercialcommercialOpen Source infoGPL V3
Cloud-based only infoOnly available as a cloud serviceyesnoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageANSI C, C++ScalaProlog, Rust
Server operating systemshostedAndroid
Linux infoARM, x86
Raspbian
Windows
hostedhostedLinux
Data schemeFlexible Schema (defined schema, partial schema, schema free)Flexible Schema (defined schema, partial schema, schema free)schema-freeFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyes, ANSI Standard SQL Typesnoyes 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.yesyesnoyesno
Secondary indexesyesyesyesall fields are automatically indexed
SQL infoSupport of SQLwith Databricks SQLyes infoANSI SQL queriesnoKusto Query Language (KQL), SQL subsetSQL-like query language (WOQL)
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
RESTful HTTP APIMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
OWL
RESTful HTTP API
WOQL (Web Object Query Language)
Supported programming languagesPython
R
Scala
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
JavaScript
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes info.Net, JavaScript, C/C++user defined functionsYes, possible languages: KQL, Python, Ryes
Triggersyesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesFile partitioning infoCustomizable business rules for partitioninghorizontal partitioning infoconsistent hashingSharding infoImplicit feature of the cloud serviceGraph Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoSynchronous and asynchronous realtime replication based on transaction logsMulti-source replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Journaling Streams
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Tunable Consistency
Immediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyes infowhen using SQLyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoin-memory journaling
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono
User concepts infoAccess controlFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Identity management, authentication, and access controlAzure Active Directory AuthenticationRole-based access control
More information provided by the system vendor
DatabricksFaircom EDGE infoformerly c-treeEDGEFauna infopreviously named FaunaDBMicrosoft Azure Data ExplorerTerminusDB infoformer name was DataChemist
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksFaircom EDGE infoformerly c-treeEDGEFauna infopreviously named FaunaDBMicrosoft Azure Data ExplorerTerminusDB infoformer name was DataChemist
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