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DBMS > Dragonfly vs. GigaSpaces vs. Hazelcast vs. Ingres vs. Microsoft Azure Data Explorer

System Properties Comparison Dragonfly vs. GigaSpaces vs. Hazelcast vs. Ingres vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameDragonfly  Xexclude from comparisonGigaSpaces  Xexclude from comparisonHazelcast  Xexclude from comparisonIngres  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionA drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instanceHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsA widely adopted in-memory data gridWell established RDBMSFully managed big data interactive analytics platform
Primary database modelKey-value storeDocument store
Object oriented DBMS infoValues are user defined objects
Key-value storeRelational DBMSRelational DBMS infocolumn oriented
Secondary database modelsGraph DBMS
Search engine
Document 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
Score0.49
Rank#261  Overall
#38  Key-value stores
Score1.03
Rank#188  Overall
#32  Document stores
#6  Object oriented 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
Websitegithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
www.gigaspaces.comhazelcast.comwww.actian.com/­databases/­ingresazure.microsoft.com/­services/­data-explorer
Technical documentationwww.dragonflydb.io/­docsdocs.gigaspaces.com/­latest/­landing.htmlhazelcast.org/­imdg/­docsdocs.actian.com/­ingresdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperDragonflyDB team and community contributorsGigaspaces TechnologiesHazelcastActian CorporationMicrosoft
Initial release2023200020081974 infooriginally developed at University Berkely in early 1970s2019
Current release1.0, March 202315.5, September 20205.3.6, November 202311.2, May 2022cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoBSL 1.1Open Source infoApache Version 2; Commercial licenses availableOpen 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++Java, C++, .NetJavaC
Server operating systemsLinuxLinux
macOS
Solaris
Windows
All OS with a Java VMAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
hosted
Data schemescheme-freeschema-freeschema-freeyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or datestrings, hashes, lists, sets, sorted sets, bit arraysyesyesyesyes 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.nono infoXML can be used for describing objects metadatayes infothe object must implement a serialization strategyno infobut tools for importing/exporting data from/to XML-files availableyes
Secondary indexesnoyesyesyesall fields are automatically indexed
SQL infoSupport of SQLnoSQL-99 for query and DML statementsSQL-like query languageyesKusto Query Language (KQL), SQL subset
APIs and other access methodsProprietary protocol infoRESP - REdis Serialization ProtocolGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
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 languagesC
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl
.Net
C++
Java
Python
Scala
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresLuayesyes infoEvent Listeners, Executor ServicesyesYes, possible languages: KQL, Python, R
Triggerspublish/subscribe channels provide some trigger functionalityyes, event driven architectureyes infoEventsyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslySharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
yes 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 methodsnoyes infoMap-Reduce pattern can be built with XAP task executorsyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of command blocks and scriptsACIDone or two-phase-commit; repeatable reads; read commitedACIDno
Concurrency infoSupport for concurrent manipulation of datayes, strict serializability by the serveryesyesyes 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.yesyesyesnono
User concepts infoAccess controlPassword-based authenticationRole-based access controlRole-based access controlfine grained access rights according to SQL-standardAzure Active Directory Authentication

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DragonflyGigaSpacesHazelcastIngresMicrosoft Azure Data Explorer
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