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DBMS > Bangdb vs. Hazelcast vs. Microsoft Azure Data Explorer vs. Percona Server for MySQL vs. Prometheus

System Properties Comparison Bangdb vs. Hazelcast vs. Microsoft Azure Data Explorer vs. Percona Server for MySQL vs. Prometheus

Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonHazelcast  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonPercona Server for MySQL  Xexclude from comparisonPrometheus  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphA widely adopted in-memory data gridFully managed big data interactive analytics platformEnhanced drop-in replacement for MySQL based on XtraDB or TokuDB storage engines with improved performance and additional diagnostic and management features.Open-source Time Series DBMS and monitoring system
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Key-value storeRelational DBMS infocolumn orientedRelational DBMSTime Series DBMS
Secondary database modelsSpatial DBMSDocument 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
Score0.16
Rank#338  Overall
#47  Document stores
#32  Graph DBMS
#31  Time Series DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score2.10
Rank#119  Overall
#57  Relational DBMS
Score7.69
Rank#50  Overall
#3  Time Series DBMS
Websitebangdb.comhazelcast.comazure.microsoft.com/­services/­data-explorerwww.percona.com/­software/­mysql-database/­percona-serverprometheus.io
Technical documentationdocs.bangdb.comhazelcast.org/­imdg/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerwww.percona.com/­downloads/­Percona-Server-LATESTprometheus.io/­docs
DeveloperSachin Sinha, BangDBHazelcastMicrosoftPercona
Initial release20122008201920082015
Current releaseBangDB 2.0, October 20215.3.6, November 2023cloud service with continuous releases8.0.36-28, 2024
License infoCommercial or Open SourceOpen Source infoBSD 3Open Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoGPL version 2Open 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, C++JavaC and C++Go
Server operating systemsLinuxAll OS with a Java VMhostedLinuxLinux
Windows
Data schemeschema-freeschema-freeFixed schema with schema-less datatypes (dynamic)yesyes
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesNumeric data only
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 strategyyesyesno infoImport of XML data possible
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialyesall fields are automatically indexedyesno
SQL infoSupport of SQLSQL like support with command line toolSQL-like query languageKusto Query Language (KQL), SQL subsetyesno
APIs and other access methodsProprietary protocol
RESTful HTTP API
JCache
JPA
Memcached protocol
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
ODBC
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Java
Python
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Ada
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Server-side scripts infoStored proceduresnoyes infoEvent Listeners, Executor ServicesYes, possible languages: KQL, Python, Ryesno
Triggersyes, Notifications (with Streaming only)yes infoEventsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesno
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)yes infoReplicated Mapyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
Source-replica replication
XtraDB Cluster
yes infoby Federation
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Immediate Consistency
Immediate Consistencynone
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitednoACIDno
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesyesyesyes
Durability infoSupport for making data persistentyes, implements WAL (Write ahead log) as wellyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes, run db with in-memory only modeyesnoyesno
User concepts infoAccess controlyes (enterprise version only)Role-based access controlAzure Active Directory AuthenticationUsers with fine-grained authorization concept infono user groups or rolesno

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More resources
BangdbHazelcastMicrosoft Azure Data ExplorerPercona Server for MySQLPrometheus
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