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DBMS > AlaSQL vs. Apache IoTDB vs. Memcached vs. Microsoft Azure Data Explorer vs. Oracle NoSQL

System Properties Comparison AlaSQL vs. Apache IoTDB vs. Memcached vs. Microsoft Azure Data Explorer vs. Oracle NoSQL

Editorial information provided by DB-Engines
NameAlaSQL  Xexclude from comparisonApache IoTDB  Xexclude from comparisonMemcached  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOracle NoSQL  Xexclude from comparison
DescriptionJavaScript DBMS libraryAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkIn-memory key-value store, originally intended for cachingFully managed big data interactive analytics platformA multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes
Primary database modelDocument store
Relational DBMS
Time Series DBMSKey-value storeRelational DBMS infocolumn orientedDocument store
Key-value store
Relational DBMS
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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.51
Rank#256  Overall
#40  Document stores
#118  Relational DBMS
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score18.08
Rank#32  Overall
#4  Key-value stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score3.05
Rank#97  Overall
#17  Document stores
#16  Key-value stores
#50  Relational DBMS
Websitealasql.orgiotdb.apache.orgwww.memcached.orgazure.microsoft.com/­services/­data-explorerwww.oracle.com/­database/­nosql/­technologies/­nosql
Technical documentationgithub.com/­AlaSQL/­alasqliotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlgithub.com/­memcached/­memcached/­wikidocs.microsoft.com/­en-us/­azure/­data-explorerdocs.oracle.com/­en/­database/­other-databases/­nosql-database/­index.html
DeveloperAndrey Gershun & Mathias R. WulffApache Software FoundationDanga Interactive infooriginally developed by Brad Fitzpatrick for LiveJournalMicrosoftOracle
Initial release20142018200320192011
Current release1.1.0, April 20231.6.27, May 2024cloud service with continuous releases23.3, December 2023
License infoCommercial or Open SourceOpen Source infoMIT-LicenseOpen Source infoApache Version 2.0Open Source infoBSD licensecommercialOpen Source infoProprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)
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 languageJavaScriptJavaCJava
Server operating systemsserver-less, requires a JavaScript environment (browser, Node.js)All OS with a Java VM (>= 1.8)FreeBSD
Linux
OS X
Unix
Windows
hostedLinux
Solaris SPARC/x86
Data schemeschema-freeyesschema-freeFixed schema with schema-less datatypes (dynamic)Support Fixed schema and Schema-less deployment with the ability to interoperate between them.
Typing infopredefined data types such as float or datenoyesnoyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesoptional
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.nonoyesno
Secondary indexesnoyesnoall fields are automatically indexedyes
SQL infoSupport of SQLClose to SQL99, but no user access control, stored procedures and host language bindings.SQL-like query languagenoKusto Query Language (KQL), SQL subsetSQL-like DML and DDL statements
APIs and other access methodsJavaScript APIJDBC
Native API
Proprietary protocolMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP API
Supported programming languagesJavaScriptC
C#
C++
Go
Java
Python
Scala
.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C#
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnoyesnoYes, possible languages: KQL, Python, Rno
Triggersyesyesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning (by time range) + vertical partitioning (by deviceId)noneSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasnone infoRepcached, a Memcached patch, provides this functionallityyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoIntegration with Hadoop and SparknoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkwith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual Consistency
Strong Consistency with Raft
Eventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency infodepending on configuration
Foreign keys infoReferential integrityyesnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infoonly for local storage and DOM-storagenononoconfigurable infoACID within a storage node (=shard)
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infoby using IndexedDB, SQL.JS or proprietary FileStorageyesnoyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyes infooff heap cache
User concepts infoAccess controlnoyesyes infousing SASL (Simple Authentication and Security Layer) protocolAzure Active Directory AuthenticationAccess rights for users and roles

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More resources
AlaSQLApache IoTDBMemcachedMicrosoft Azure Data ExplorerOracle NoSQL
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