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DBMS > EJDB vs. Fauna vs. Fujitsu Enterprise Postgres vs. Microsoft Azure Data Explorer

System Properties Comparison EJDB vs. Fauna vs. Fujitsu Enterprise Postgres vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
NameEJDB  Xexclude from comparisonFauna infopreviously named FaunaDB  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionEmbeddable document-store database library with JSON representation of queries (in MongoDB style)Fauna 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.Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.Fully managed big data interactive analytics platform
Primary database modelDocument storeDocument store
Graph DBMS
Relational DBMS
Time Series DBMS
Relational DBMSRelational DBMS infocolumn oriented
Secondary database modelsDocument store
Spatial DBMS
Document 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
Score0.27
Rank#297  Overall
#44  Document stores
Score1.52
Rank#153  Overall
#26  Document stores
#14  Graph DBMS
#71  Relational DBMS
#13  Time Series DBMS
Score0.31
Rank#285  Overall
#129  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websitegithub.com/­Softmotions/­ejdbfauna.comwww.postgresql.fastware.comazure.microsoft.com/­services/­data-explorer
Technical documentationgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mddocs.fauna.comwww.postgresql.fastware.com/­product-manualsdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperSoftmotionsFauna, Inc.PostgreSQL Global Development Group, Fujitsu Australia Software TechnologyMicrosoft
Initial release201220142019
Current releaseFujitsu Enterprise Postgres 14, January 2022cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoGPLv2commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCScalaC
Server operating systemsserver-lesshostedLinux
Windows
hosted
Data schemeschema-freeschema-freeyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyes infostring, integer, double, bool, date, object_idnoyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
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.noyes
Secondary indexesnoyesyesall fields are automatically indexed
SQL infoSupport of SQLnonoyesKusto Query Language (KQL), SQL subset
APIs and other access methodsin-process shared libraryRESTful HTTP APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesActionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnouser defined functionsuser defined functionsYes, possible languages: KQL, Python, R
Triggersnonoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning infoconsistent hashingpartitioning by range, list and by hashSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replicationSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityno infotypically not needed, however similar functionality with collection joins possibleyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayes infoRead/Write Lockingyesyes, multi-version concurrency control (MVCC)yes
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.nono
User concepts infoAccess controlnoIdentity management, authentication, and access controlfine grained access rights according to SQL-standardAzure Active Directory Authentication
More information provided by the system vendor
EJDBFauna infopreviously named FaunaDBFujitsu Enterprise PostgresMicrosoft Azure Data Explorer
Specific characteristics100% compatible with community PostgreSQL
» more
Competitive advantagesBuilt-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more
Typical application scenariosTransactional payments applications, reporting and mixed workloads.
» more
Market metricsOver 30 years experience in database technology. Over 20 years in Postgres development...
» more
Licensing and pricing modelsCore based licensing
» more

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More resources
EJDBFauna infopreviously named FaunaDBFujitsu Enterprise PostgresMicrosoft Azure Data Explorer
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