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DBMS > atoti vs. EsgynDB vs. Memcached vs. Microsoft Azure Data Explorer vs. Weaviate

System Properties Comparison atoti vs. EsgynDB vs. Memcached vs. Microsoft Azure Data Explorer vs. Weaviate

Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonEsgynDB  Xexclude from comparisonMemcached  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonWeaviate  Xexclude from comparison
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.Enterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionIn-memory key-value store, originally intended for cachingFully managed big data interactive analytics platformAn AI-native realtime vector database engine that integrates scalable machine learning models.
Primary database modelObject oriented DBMSRelational DBMSKey-value storeRelational DBMS infocolumn orientedVector 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
Score0.56
Rank#245  Overall
#10  Object oriented DBMS
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score19.42
Rank#32  Overall
#4  Key-value stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score1.73
Rank#143  Overall
#5  Vector DBMS
Websiteatoti.iowww.esgyn.cnwww.memcached.orgazure.microsoft.com/­services/­data-explorergithub.com/­weaviate/­weaviate
weaviate.io
Technical documentationdocs.atoti.iogithub.com/­memcached/­memcached/­wikidocs.microsoft.com/­en-us/­azure/­data-explorerweaviate.io/­developers/­weaviate
DeveloperActiveViamEsgynDanga Interactive infooriginally developed by Brad Fitzpatrick for LiveJournalMicrosoftWeaviate B.V.
Initial release2015200320192019
Current release1.6.25, March 2024cloud service with continuous releases1.19, May 2023
License infoCommercial or Open Sourcecommercial infofree versions availablecommercialOpen Source infoBSD licensecommercialOpen Source infocommercial license available with Weaviate Enterprise
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 languageJavaC++, JavaCGo
Server operating systemsLinuxFreeBSD
Linux
OS X
Unix
Windows
hosted
Data schemeyesschema-freeFixed schema with schema-less datatypes (dynamic)yes, maps to GraphQL interface
Typing infopredefined data types such as float or dateyesnoyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes infostring, int, float, geo point, date, cross reference, fuzzy references
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.noyesno
Secondary indexesyesnoall fields are automatically indexedyes infoall data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed
SQL infoSupport of SQLMultidimensional Expressions (MDX)yesnoKusto Query Language (KQL), SQL subsetGraphQL is used as query language
APIs and other access methodsADO.NET
JDBC
ODBC
Proprietary protocolMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
GraphQL query language
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.Net.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
JavaScript / TypeScript
Python
Server-side scripts infoStored proceduresPythonJava Stored ProceduresnoYes, possible languages: KQL, Python, Rno
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningShardingnoneSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersnone infoRepcached, a Memcached patch, provides this functionallityyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonono
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyesyes
Durability infoSupport for making data persistentyesnoyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardyes infousing SASL (Simple Authentication and Security Layer) protocolAzure Active Directory AuthenticationAPI Keys
OpenID Connect Discovery
More information provided by the system vendor
atotiEsgynDBMemcachedMicrosoft Azure Data ExplorerWeaviate
Specific characteristicsWeaviate is an open source vector database that is robust, scalable, cloud-native,...
» more
Competitive advantagesFlexible deployment - Free, open source or fully-managed cloud vector database service...
» more
Typical application scenariosAs a database supporting the development of generative AI and semantic search applications...
» more
Key customersAll companies that have data. ​
» more
Market metricsAs of mid 2023: Over 2 million open source downloads 3500+ Weaviate Slack community...
» more
Licensing and pricing modelsWeaviate is open-source, and free to use. Weaviate is also available as a fully managed...
» more

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atotiEsgynDBMemcachedMicrosoft Azure Data ExplorerWeaviate
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