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DBMS > atoti vs. Microsoft Azure Data Explorer vs. Oracle Berkeley DB vs. Weaviate

System Properties Comparison atoti vs. Microsoft Azure Data Explorer vs. Oracle Berkeley DB vs. Weaviate

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Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonWeaviate  Xexclude from comparison
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.Fully managed big data interactive analytics platformWidely used in-process key-value storeAn AI-native realtime vector database engine that integrates scalable machine learning models.
Primary database modelObject oriented DBMSRelational DBMS infocolumn orientedKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Vector 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
Score0.45
Rank#253  Overall
#13  Object oriented DBMS
Score3.28
Rank#83  Overall
#45  Relational DBMS
Score1.88
Rank#130  Overall
#23  Key-value stores
#3  Native XML DBMS
Score1.48
Rank#149  Overall
#8  Vector DBMS
Websiteatoti.ioazure.microsoft.com/­services/­data-explorerwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlgithub.com/­weaviate/­weaviate
weaviate.io
Technical documentationdocs.atoti.iodocs.microsoft.com/­en-us/­azure/­data-explorerdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlweaviate.io/­developers/­weaviate
DeveloperActiveViamMicrosoftOracle infooriginally developed by Sleepycat, which was acquired by OracleWeaviate B.V.
Initial release201919942019
Current releasecloud service with continuous releases18.1.40, May 20201.19, May 2023
License infoCommercial or Open Sourcecommercial infofree versions availablecommercialOpen Source infocommercial license availableOpen Source infocommercial license available with Weaviate Enterprise
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC, Java, C++ (depending on the Berkeley DB edition)Go
Server operating systemshostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Data schemeFixed schema with schema-less datatypes (dynamic)schema-freeyes, maps to GraphQL interface
Typing infopredefined data types such as float or dateyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesnoyes 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.yesyes infoonly with the Berkeley DB XML editionno
Secondary indexesall fields are automatically indexedyesyes infoall data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed
SQL infoSupport of SQLMultidimensional Expressions (MDX)Kusto Query Language (KQL), SQL subsetyes infoSQL interfaced based on SQLite is availableGraphQL is used as query language
APIs and other access methodsMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
GraphQL query language
RESTful HTTP/JSON API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
JavaScript / TypeScript
Python
Server-side scripts infoStored proceduresPythonYes, possible languages: KQL, Python, Rnono
Triggersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoonly for the SQL APIno
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningSharding infoImplicit feature of the cloud servicenoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesyes
User concepts infoAccess controlAzure Active Directory AuthenticationnoAPI Keys
OpenID Connect Discovery
More information provided by the system vendor
atotiMicrosoft Azure Data ExplorerOracle Berkeley DBWeaviate
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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More resources
atotiMicrosoft Azure Data ExplorerOracle Berkeley DBWeaviate
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