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DBMS > EsgynDB vs. FoundationDB vs. Hazelcast vs. Ingres vs. Microsoft Azure Data Explorer

System Properties Comparison EsgynDB vs. FoundationDB vs. Hazelcast vs. Ingres vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonFoundationDB  Xexclude from comparisonHazelcast  Xexclude from comparisonIngres  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionOrdered key-value store. Core features are complimented by layers.A widely adopted in-memory data gridWell established RDBMSFully managed big data interactive analytics platform
Primary database modelRelational DBMSDocument store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Key-value storeRelational DBMSRelational DBMS infocolumn oriented
Secondary database modelsDocument store infoJSON support with IMDG 3.12Document 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
Score1.06
Rank#185  Overall
#31  Document stores
#28  Key-value stores
#85  Relational DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score3.80
Rank#82  Overall
#44  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websitewww.esgyn.cngithub.com/­apple/­foundationdbhazelcast.comwww.actian.com/­databases/­ingresazure.microsoft.com/­services/­data-explorer
Technical documentationapple.github.io/­foundationdbhazelcast.org/­imdg/­docsdocs.actian.com/­ingresdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperEsgynFoundationDBHazelcastActian CorporationMicrosoft
Initial release2015201320081974 infooriginally developed at University Berkely in early 1970s2019
Current release6.2.28, November 20205.3.6, November 202311.2, May 2022cloud service with continuous releases
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache Version 2; commercial licenses availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaC++JavaC
Server operating systemsLinuxLinux
OS X
Windows
All OS with a Java VMAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
hosted
Data schemeyesschema-free infosome layers support schemasschema-freeyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesno infosome layers support typingyesyesyes 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 infothe object must implement a serialization strategyno infobut tools for importing/exporting data from/to XML-files availableyes
Secondary indexesyesnoyesyesall fields are automatically indexed
SQL infoSupport of SQLyessupported in specific SQL layer onlySQL-like query languageyesKusto Query Language (KQL), SQL subset
APIs and other access methodsADO.NET
JDBC
ODBC
JCache
JPA
Memcached protocol
RESTful HTTP API
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.Net.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresJava Stored Proceduresin SQL-layer onlyyes infoEvent Listeners, Executor ServicesyesYes, possible languages: KQL, Python, R
Triggersnonoyes infoEventsyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslySharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersyesyes infoReplicated MapIngres Replicatoryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyLinearizable consistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesin SQL-layer onlynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDone or two-phase-commit; repeatable reads; read commitedACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoMVCCyes
Durability infoSupport for making data persistentyesyesyesyesyes
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-standardnoRole-based access controlfine grained access rights according to SQL-standardAzure Active Directory Authentication

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More resources
EsgynDBFoundationDBHazelcastIngresMicrosoft Azure Data Explorer
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