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DBMS > Databend vs. Elasticsearch vs. EsgynDB vs. Microsoft Azure Data Explorer vs. Riak KV

System Properties Comparison Databend vs. Elasticsearch vs. EsgynDB vs. Microsoft Azure Data Explorer vs. Riak KV

Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonElasticsearch  Xexclude from comparisonEsgynDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRiak KV  Xexclude from comparison
DescriptionAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityA distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionFully managed big data interactive analytics platformDistributed, fault tolerant key-value store
Primary database modelRelational DBMSSearch engineRelational DBMSRelational DBMS infocolumn orientedKey-value store infowith links between data sets and object tags for the creation of secondary indexes
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
Document 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
Score0.34
Rank#283  Overall
#130  Relational DBMS
Score132.83
Rank#7  Overall
#1  Search engines
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score4.01
Rank#79  Overall
#9  Key-value stores
Websitegithub.com/­datafuselabs/­databend
www.databend.com
www.elastic.co/­elasticsearchwww.esgyn.cnazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.databend.comwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmldocs.microsoft.com/­en-us/­azure/­data-explorerwww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperDatabend LabsElasticEsgynMicrosoftOpenSource, formerly Basho Technologies
Initial release20212010201520192009
Current release1.0.59, April 20238.6, January 2023cloud service with continuous releases3.2.0, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoElastic LicensecommercialcommercialOpen Source infoApache version 2, commercial enterprise edition
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageRustJavaC++, JavaErlang
Server operating systemshosted
Linux
macOS
All OS with a Java VMLinuxhostedLinux
OS X
Data schemeyesschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesFixed schema with schema-less datatypes (dynamic)schema-free
Typing infopredefined data types such as float or dateyesyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesno
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.nononoyesno
Secondary indexesnoyes infoAll search fields are automatically indexedyesall fields are automatically indexedrestricted
SQL infoSupport of SQLyesSQL-like query languageyesKusto Query Language (KQL), SQL subsetno
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
Java API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP API
Native Erlang Interface
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
All languages supporting JDBC/ODBC/ADO.Net.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Server-side scripts infoStored proceduresnoyesJava Stored ProceduresYes, possible languages: KQL, Python, RErlang
Triggersnoyes infoby using the 'percolation' featurenoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding infoImplicit feature of the cloud serviceSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyesMulti-source replication between multi datacentersyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoES-Hadoop ConnectoryesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integritynonoyesnono infolinks between data sets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.Memcached and Redis integrationnono
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesfine grained access rights according to SQL-standardAzure Active Directory Authenticationyes, using Riak Security

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More resources
DatabendElasticsearchEsgynDBMicrosoft Azure Data ExplorerRiak KV
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