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DBMS > EsgynDB vs. GBase vs. Microsoft Azure Data Explorer vs. Tigris

System Properties Comparison EsgynDB vs. GBase vs. Microsoft Azure Data Explorer vs. Tigris

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGBase  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTigris  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionWidely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.Fully managed big data interactive analytics platformA horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructure
Primary database modelRelational DBMSRelational DBMSRelational DBMS infocolumn orientedDocument store
Key-value store
Search engine
Time Series 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
Score1.05
Rank#186  Overall
#86  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.09
Rank#363  Overall
#49  Document stores
#54  Key-value stores
#22  Search engines
#38  Time Series DBMS
Websitewww.esgyn.cnwww.gbase.cnazure.microsoft.com/­services/­data-explorerwww.tigrisdata.com
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorerwww.tigrisdata.com/­docs
DeveloperEsgynGeneral Data Technology Co., Ltd.MicrosoftTigris Data, Inc.
Initial release2015200420192022
Current releaseGBase 8a, GBase 8s, GBase 8ccloud service with continuous releases
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaC, Java, Python
Server operating systemsLinuxLinuxhostedLinux
macOS
Windows
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)yes
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-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.noyesyesno
Secondary indexesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLyesStandard with numerous extensionsKusto Query Language (KQL), SQL subsetno
APIs and other access methodsADO.NET
JDBC
ODBC
ADO.NET
C API
JDBC
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
CLI Client
gRPC
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC#.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Go
Java
JavaScript (Node.js)
Server-side scripts infoStored proceduresJava Stored Proceduresuser defined functionsYes, possible languages: KQL, Python, Rno
Triggersnoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by range, list and hash) and vertical partitioningSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes, using FoundationDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlfine grained access rights according to SQL-standardyesAzure Active Directory AuthenticationAccess rights for users and roles

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More resources
EsgynDBGBaseMicrosoft Azure Data ExplorerTigris
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