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DBMS > Apache Druid vs. GigaSpaces vs. Microsoft Azure Data Explorer vs. SwayDB vs. Weaviate

System Properties Comparison Apache Druid vs. GigaSpaces vs. Microsoft Azure Data Explorer vs. SwayDB vs. Weaviate

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGigaSpaces  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSwayDB  Xexclude from comparisonWeaviate  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsFully managed big data interactive analytics platformAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storageAn AI-native realtime vector database engine that integrates scalable machine learning models.
Primary database modelRelational DBMS
Time Series DBMS
Document store
Object oriented DBMS infoValues are user defined objects
Relational DBMS infocolumn orientedKey-value storeVector DBMS
Secondary database modelsGraph DBMS
Search engine
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
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score1.03
Rank#188  Overall
#32  Document stores
#6  Object oriented DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.04
Rank#387  Overall
#61  Key-value stores
Score1.52
Rank#153  Overall
#5  Vector DBMS
Websitedruid.apache.orgwww.gigaspaces.comazure.microsoft.com/­services/­data-explorerswaydb.simer.augithub.com/­weaviate/­weaviate
weaviate.io
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.gigaspaces.com/­latest/­landing.htmldocs.microsoft.com/­en-us/­azure/­data-explorerweaviate.io/­developers/­weaviate
DeveloperApache Software Foundation and contributorsGigaspaces TechnologiesMicrosoftSimer PlahaWeaviate B.V.
Initial release20122000201920182019
Current release29.0.1, April 202415.5, September 2020cloud service with continuous releases1.19, May 2023
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2; Commercial licenses availablecommercialOpen Source infoGNU Affero GPL V3.0Open Source infocommercial license available with Weaviate Enterprise
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava, C++, .NetScalaGo
Server operating systemsLinux
OS X
Unix
Linux
macOS
Solaris
Windows
hosted
Data schemeyes infoschema-less columns are supportedschema-freeFixed schema with schema-less datatypes (dynamic)schema-freeyes, maps to GraphQL interface
Typing infopredefined data types such as float or dateyesyesyes 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.nono infoXML can be used for describing objects metadatayesnono
Secondary indexesyesyesall fields are automatically indexednoyes infoall data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed
SQL infoSupport of SQLSQL for queryingSQL-99 for query and DML statementsKusto Query Language (KQL), SQL subsetnoGraphQL is used as query language
APIs and other access methodsJDBC
RESTful HTTP/JSON API
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
GraphQL query language
RESTful HTTP/JSON API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
C++
Java
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Java
Kotlin
Scala
JavaScript / TypeScript
Python
Server-side scripts infoStored proceduresnoyesYes, possible languages: KQL, Python, Rnono
Triggersnoyes, event driven architectureyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingSharding infoImplicit feature of the cloud servicenoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.noneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoMap-Reduce pattern can be built with XAP task executorsSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYEventual Consistency
Immediate Consistency
Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoAtomic execution of operationsno
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.noyesnoyesyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemRole-based access controlAzure Active Directory AuthenticationnoAPI Keys
OpenID Connect Discovery
More information provided by the system vendor
Apache DruidGigaSpacesMicrosoft Azure Data ExplorerSwayDBWeaviate
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...
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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
Apache DruidGigaSpacesMicrosoft Azure Data ExplorerSwayDBWeaviate
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