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DBMS > HarperDB vs. Microsoft Azure Data Explorer vs. Newts vs. Quasardb vs. Solr

System Properties Comparison HarperDB vs. Microsoft Azure Data Explorer vs. Newts vs. Quasardb vs. Solr

Editorial information provided by DB-Engines
NameHarperDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonNewts  Xexclude from comparisonQuasardb  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionUltra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.Fully managed big data interactive analytics platformTime Series DBMS based on CassandraDistributed, high-performance timeseries databaseA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelDocument storeRelational DBMS infocolumn orientedTime Series DBMSTime Series DBMSSearch engine
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
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.55
Rank#248  Overall
#38  Document stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websitewww.harperdb.ioazure.microsoft.com/­services/­data-exploreropennms.github.io/­newtsquasar.aisolr.apache.org
Technical documentationdocs.harperdb.io/­docsdocs.microsoft.com/­en-us/­azure/­data-explorergithub.com/­OpenNMS/­newts/­wikidoc.quasar.ai/­mastersolr.apache.org/­resources.html
DeveloperHarperDBMicrosoftOpenNMS GroupquasardbApache Software Foundation
Initial release20172019201420092006
Current release3.1, August 2021cloud service with continuous releases3.14.1, January 20249.6.0, April 2024
License infoCommercial or Open Sourcecommercial infofree community edition availablecommercialOpen Source infoApache 2.0commercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageNode.jsJavaC++Java
Server operating systemsLinux
OS X
hostedLinux
OS X
Windows
BSD
Linux
OS X
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemedynamic schemaFixed schema with schema-less datatypes (dynamic)schema-freeschema-freeyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyes infoJSON data typesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyes infointeger and binaryyes infosupports customizable data types and automatic typing
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.noyesnonoyes
Secondary indexesyesall fields are automatically indexednoyes infowith tagsyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL-like data manipulation statementsKusto Query Language (KQL), SQL subsetnoSQL-like query languageSolr Parallel SQL Interface
APIs and other access methodsJDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP REST
Java API
HTTP APIJava API
RESTful HTTP/JSON API
Supported programming languages.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Java.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresCustom Functions infosince release 3.1Yes, possible languages: KQL, Python, RnonoJava plugins
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynonoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesA table resides as a whole on one (or more) nodes in a clusterSharding infoImplicit feature of the cloud serviceSharding infobased on CassandraSharding infoconsistent hashingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infothe nodes on which a table resides can be definedyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factor infobased on CassandraSource-replica replication with selectable replication factoryes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknowith Hadoop integrationspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsnonoACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes, using LMDByesyesyes infoby using LevelDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes infoTransient modeyes
User concepts infoAccess controlAccess rights for users and rolesAzure Active Directory AuthenticationnoCryptographically strong user authentication and audit trailyes

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HarperDBMicrosoft Azure Data ExplorerNewtsQuasardbSolr
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