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DBMS > DolphinDB vs. Microsoft Azure Data Explorer vs. Sqrrl vs. Warp 10 vs. Weaviate

System Properties Comparison DolphinDB vs. Microsoft Azure Data Explorer vs. Sqrrl vs. Warp 10 vs. Weaviate

Editorial information provided by DB-Engines
NameDolphinDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSqrrl  Xexclude from comparisonWarp 10  Xexclude from comparisonWeaviate  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionDolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.Fully managed big data interactive analytics platformAdaptable, secure NoSQL built on Apache AccumuloTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBaseAn AI-native realtime vector database engine that integrates scalable machine learning models.
Primary database modelTime Series DBMSRelational DBMS infocolumn orientedDocument store
Graph DBMS
Key-value store
Wide column store
Time Series DBMSVector DBMS
Secondary database modelsRelational DBMSDocument 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
Score4.13
Rank#80  Overall
#6  Time Series DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.07
Rank#349  Overall
#32  Time Series DBMS
Score1.73
Rank#143  Overall
#5  Vector DBMS
Websitewww.dolphindb.comazure.microsoft.com/­services/­data-explorersqrrl.comwww.warp10.iogithub.com/­weaviate/­weaviate
weaviate.io
Technical documentationdocs.dolphindb.cn/­en/­help200/­index.htmldocs.microsoft.com/­en-us/­azure/­data-explorerwww.warp10.io/­content/­02_Getting_startedweaviate.io/­developers/­weaviate
DeveloperDolphinDB, IncMicrosoftAmazon infooriginally Sqrrl Data, Inc.SenXWeaviate B.V.
Initial release20182019201220152019
Current releasev2.00.4, January 2022cloud service with continuous releases1.19, May 2023
License infoCommercial or Open Sourcecommercial infofree community version availablecommercialcommercialOpen Source infoApache License 2.0Open Source infocommercial license available with Weaviate Enterprise
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 languageC++JavaJavaGo
Server operating systemsLinux
Windows
hostedLinuxLinux
OS X
Windows
Data schemeyesFixed schema with schema-less datatypes (dynamic)schema-freeschema-freeyes, maps to GraphQL interface
Typing infopredefined data types such as float or dateyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyesyes 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.noyesnono
Secondary indexesyesall fields are automatically indexedyesnoyes infoall data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed
SQL infoSupport of SQLSQL-like query languageKusto Query Language (KQL), SQL subsetnonoGraphQL is used as query language
APIs and other access methodsJDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
HTTP API
Jupyter
WebSocket
GraphQL query language
RESTful HTTP/JSON API
Supported programming languagesC#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
JavaScript / TypeScript
Python
Server-side scripts infoStored proceduresyesYes, possible languages: KQL, Python, Rnoyes infoWarpScriptno
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynonono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningSharding infoImplicit feature of the cloud serviceSharding infomaking use of HadoopSharding infobased on HBaseSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factor infomaking use of Hadoopselectable replication factor infobased on HBaseyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.Immediate Consistency infobased on HBaseEventual Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnoAtomic updates per row, document, or graph entitynono
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.yesnoyesyes
User concepts infoAccess controlAdministrators, Users, GroupsAzure Active Directory AuthenticationCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)Mandatory use of cryptographic tokens, containing fine-grained authorizationsAPI Keys
OpenID Connect Discovery
More information provided by the system vendor
DolphinDBMicrosoft Azure Data ExplorerSqrrlWarp 10Weaviate
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
DolphinDBMicrosoft Azure Data ExplorerSqrrlWarp 10Weaviate
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