DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Qdrant vs. Sadas Engine vs. SiriDB vs. Spark SQL

System Properties Comparison Qdrant vs. Sadas Engine vs. SiriDB vs. Spark SQL

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameQdrant  Xexclude from comparisonSadas Engine  Xexclude from comparisonSiriDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA high-performance vector database with neural network or semantic-based matchingSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsOpen Source Time Series DBMSSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelVector DBMSRelational DBMSTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.28
Rank#167  Overall
#7  Vector DBMS
Score0.07
Rank#373  Overall
#157  Relational DBMS
Score0.07
Rank#378  Overall
#42  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­qdrant/­qdrant
qdrant.tech
www.sadasengine.comsiridb.comspark.apache.org/­sql
Technical documentationqdrant.tech/­documentationwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationdocs.siridb.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperQdrantSADAS s.r.l.CesbitApache Software Foundation
Initial release2021200620172014
Current release8.03.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infofree trial version availableOpen Source infoMIT LicenseOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageRustC++CScala
Server operating systemsDocker
Linux
macOS
Windows
AIX
Linux
Windows
LinuxLinux
OS X
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateNumbers, Strings, Geo, Booleanyesyes infoNumeric datayes
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.nononono
Secondary indexesyes infoKeywords, numberic ranges, geo, full-textyesyesno
SQL infoSupport of SQLnoyesnoSQL-like DML and DDL statements
APIs and other access methodsgRPC
OpenAPI 3.0
RESTful HTTP/JSON API infoOpenAPI 3.0
JDBC
ODBC
Proprietary protocol
HTTP APIJDBC
ODBC
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
Python
Rust
.Net
C
C#
C++
Groovy
Java
PHP
Python
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesCollection-level replicationnoneyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency, tunable consistencyImmediate Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infomanaged by 'Learn by Usage'yesno
User concepts infoAccess controlKey-based authenticationAccess rights for users, groups and roles according to SQL-standardsimple rights management via user accountsno

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
QdrantSadas EngineSiriDBSpark SQL
Recent citations in the news

Open source vector database startup Qdrant raises $28M
23 January 2024, TechCrunch

Qdrant Raises $28M to Advance Massive-Scale AI Applications
23 January 2024, businesswire.com

Qdrant Hybrid Cloud is Now Available for OCI Customers: Managed Vector Search Engine for Data-Sensitive AI ...
16 April 2024, blogs.oracle.com

Qdrant offers managed vector database for hybrid clouds
16 April 2024, InfoWorld

Why Vector Data Services For AI Are A Moveable Feast
17 April 2024, Forbes

provided by Google News

Use Amazon Athena with Spark SQL for your open-source transactional table formats | Amazon Web Services
24 January 2024, AWS Blog

What is Apache Spark? The big data platform that crushed Hadoop
3 April 2024, InfoWorld

Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2024
1 April 2024, Simplilearn

Performant IPv4 Range Spark Joins | by Jean-Claude Cote
24 January 2024, Towards Data Science

Simba Technologies(R) Introduces New, Powerful JDBC Driver With SQL Connector for Apache Spark(TM)
17 March 2024, Yahoo Singapore News

provided by Google News



Share this page

Featured Products

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Present your product here