DB-EnginesExtremeDB: mitigate connectivity issues in a DBMSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > EsgynDB vs. GridGain vs. Microsoft Azure Data Explorer vs. TinkerGraph vs. Trafodion

System Properties Comparison EsgynDB vs. GridGain vs. Microsoft Azure Data Explorer vs. TinkerGraph vs. Trafodion

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGridGain  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTinkerGraph  Xexclude from comparisonTrafodion  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionGridGain is an in-memory computing platform, built on Apache IgniteFully managed big data interactive analytics platformA lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 APITransactional SQL-on-Hadoop DBMS
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMS infocolumn orientedGraph 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
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.08
Rank#348  Overall
#35  Graph DBMS
Websitewww.esgyn.cnwww.gridgain.comazure.microsoft.com/­services/­data-explorertinkerpop.apache.org/­docs/­current/­reference/­#tinkergraph-gremlintrafodion.apache.org
Technical documentationwww.gridgain.com/­docs/­index.htmldocs.microsoft.com/­en-us/­azure/­data-explorertrafodion.apache.org/­documentation.html
DeveloperEsgynGridGain Systems, Inc.MicrosoftApache Software Foundation, originally developed by HP
Initial release20152007201920092014
Current releaseGridGain 8.5.1cloud service with continuous releases2.3.0, February 2019
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache 2.0Open Source infoApache 2.0
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++, JavaJava, C++, .NetJavaC++, Java
Server operating systemsLinuxLinux
OS X
Solaris
Windows
hostedLinux
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)schema-freeyes
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-typesyesyes
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.noyesyesnono
Secondary indexesyesyesall fields are automatically indexednoyes
SQL infoSupport of SQLyesANSI-99 for query and DML statements, subset of DDLKusto Query Language (KQL), SQL subsetnoyes
APIs and other access methodsADO.NET
JDBC
ODBC
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
TinkerPop 3ADO.NET
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC#
C++
Java
PHP
Python
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Groovy
Java
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresJava Stored Proceduresyes (compute grid and cache interceptors can be used instead)Yes, possible languages: KQL, Python, RnoJava Stored Procedures
Triggersnoyes (cache interceptors and events)yes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud servicenoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersyes (replicated cache)yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.noneyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes (compute grid and hadoop accelerator)Spark connector (open source): github.com/­Azure/­azure-kusto-sparknoyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
noneImmediate Consistency
Foreign keys infoReferential integrityyesnonoyes infoRelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesnoyes
Durability infoSupport for making data persistentyesyesyesoptionalyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardSecurity Hooks for custom implementationsAzure Active Directory Authenticationnofine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
EsgynDBGridGainMicrosoft Azure Data ExplorerTinkerGraphTrafodion
Recent citations in the news

GridGain in-memory data and generative AI – Blocks and Files
10 May 2024, Blocks & Files

GridGain Announces Call for Speakers for Virtual Apache Ignite Summit 2024
8 February 2024, PR Newswire

GridGain's 2023 Growth Positions Company for Strong 2024
24 January 2024, PR Newswire

GridGain Adds Andy Sacks as Chief Revenue Officer, Promotes Lalit Ahuja to Chief Customer and Product Officer ...
17 July 2023, Yahoo Finance

GridGain: Product Overview and Analysis
5 June 2019, eWeek

provided by Google News

Azure Data Explorer: Log and telemetry analytics benchmark
16 August 2022, Microsoft

Controlling costs in Azure Data Explorer using down-sampling and aggregation
11 February 2019, Microsoft

Providing modern data transfer and storage service at Microsoft with Microsoft Azure - Inside Track Blog
13 July 2023, Microsoft

Microsoft Introduces Azure Integration Environments and Business Process Tracking in Public Preview
23 November 2023, InfoQ.com

Individually great, collectively unmatched: Announcing updates to 3 great Azure Data Services
7 February 2019, Microsoft

provided by Google News

Why developers like Apache TinkerPop, an open source framework for graph computing | Amazon Web Services
27 September 2021, AWS Blog

Introducing Gremlin query hints for Amazon Neptune
26 February 2019, AWS Blog

InfiniteGraph Gets Support for Common Graph Database Language and More
21 February 2012, SiliconANGLE News

provided by Google News

SQL-on-Hadoop Database Trafodion Bridges Transactions and Analysis
24 January 2018, The New Stack

Evaluating HTAP Databases for Machine Learning Applications
2 November 2016, KDnuggets

Low-latency, distributed database architectures are critical for emerging fog applications
7 April 2022, Embedded Computing Design

provided by Google News



Share this page

Featured Products

SingleStore logo

Build AI apps with Vectors on SQL and JSON with milliseconds response times.
Try it today.

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Present your product here