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DBMS > EsgynDB vs. Faircom EDGE vs. Microsoft Azure Data Explorer vs. NSDb vs. Teradata Aster

System Properties Comparison EsgynDB vs. Faircom EDGE vs. Microsoft Azure Data Explorer vs. NSDb vs. Teradata Aster

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonNSDb  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsFully managed big data interactive analytics platformScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesPlatform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMS infocolumn orientedTime Series 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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score0.09
Rank#362  Overall
#53  Key-value stores
#155  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.08
Rank#369  Overall
#40  Time Series DBMS
Websitewww.esgyn.cnwww.faircom.com/­products/­faircom-edgeazure.microsoft.com/­services/­data-explorernsdb.io
Technical documentationdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmldocs.microsoft.com/­en-us/­azure/­data-explorernsdb.io/­Architecture
DeveloperEsgynFairCom CorporationMicrosoftTeradata
Initial release20151979201920172005
Current releaseV3, October 2020cloud service with continuous releases
License infoCommercial or Open Sourcecommercialcommercial infoRestricted, free version availablecommercialOpen Source infoApache Version 2.0commercial
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.
Implementation languageC++, JavaANSI C, C++Java, Scala
Server operating systemsLinuxAndroid
Linux infoARM, x86
Raspbian
Windows
hostedLinux
macOS
Linux
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)Fixed schema with schema-less datatypes (dynamic)Flexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesyes, ANSI Standard SQL Typesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes: int, bigint, decimal, stringyes
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.noyesyesnoyes infoin Aster File Store
Secondary indexesyesyesall fields are automatically indexedall fields are automatically indexedyes
SQL infoSupport of SQLyesyes infoANSI SQL queriesKusto Query Language (KQL), SQL subsetSQL-like query languageyes
APIs and other access methodsADO.NET
JDBC
ODBC
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
gRPC
HTTP REST
WebSocket
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC
C#
C++
Java
JavaScript
PHP
Python
VB.Net
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Java
Scala
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresJava Stored Proceduresyes info.Net, JavaScript, C/C++Yes, possible languages: KQL, Python, RnoR packages
Triggersnoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingFile partitioning infoCustomizable business rules for partitioningSharding infoImplicit feature of the cloud serviceShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersyes infoSynchronous and asynchronous realtime replication based on transaction logsyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Tunable Consistency
Eventual Consistency
Immediate Consistency
Eventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesyes infowhen using SQLnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyesyesyes
Durability infoSupport for making data persistentyesyesyesUsing Apache Luceneyes
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 access rights according to SQL-standardFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Azure Active Directory Authenticationfine grained access rights according to SQL-standard

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More resources
EsgynDBFaircom EDGE infoformerly c-treeEDGEMicrosoft Azure Data ExplorerNSDbTeradata Aster
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