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DBMS > EsgynDB vs. HEAVY.AI vs. Qdrant

System Properties Comparison EsgynDB vs. HEAVY.AI vs. Qdrant

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonQdrant  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareA high-performance vector database with neural network or semantic-based matching
Primary database modelRelational DBMSRelational DBMSVector DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#328  Overall
#145  Relational DBMS
Score1.52
Rank#147  Overall
#67  Relational DBMS
Score1.26
Rank#163  Overall
#7  Vector DBMS
Websitewww.esgyn.cngithub.com/­heavyai/­heavydb
www.heavy.ai
github.com/­qdrant/­qdrant
qdrant.tech
Technical documentationdocs.heavy.aiqdrant.tech/­documentation
DeveloperEsgynHEAVY.AI, Inc.Qdrant
Initial release201520162021
Current release5.10, January 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; enterprise edition availableOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaC++ and CUDARust
Server operating systemsLinuxLinuxDocker
Linux
macOS
Windows
Data schemeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesNumbers, Strings, Geo, Boolean
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.nonono
Secondary indexesyesnoyes infoKeywords, numberic ranges, geo, full-text
SQL infoSupport of SQLyesyesno
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
Thrift
Vega
gRPC
OpenAPI 3.0
RESTful HTTP/JSON API infoOpenAPI 3.0
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetAll languages supporting JDBC/ODBC/Thrift
Python
.Net
Go
Java
JavaScript (Node.js)
Python
Rust
Server-side scripts infoStored proceduresJava Stored Proceduresno
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoRound robinSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersMulti-source replicationCollection-level replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency, tunable consistency
Foreign keys infoReferential integrityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.noyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardKey-based authentication

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More resources
EsgynDBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Qdrant
Recent citations in the news

HEAVY.AI Launches HEAVY 7.0, Introducing Real-Time Machine Learning Capabilities
19 April 2023, businesswire.com

OmniSci Gets HEAVY New Name and New CEO
1 March 2022, Datanami

Making the most of geospatial intelligence
14 April 2023, InfoWorld

Big Data Analytics: A Game Changer for Infrastructure
13 July 2023, Spiceworks News and Insights

Metaphysic Deep Fakes TED
3 May 2023, Forbes

provided by Google News

Qdrant Introduces BM42: Hybrid Search For Enhanced RAG
6 July 2024, Forbes

Qdrant unveils hybrid vector algorithm for improved RAG
2 July 2024, Blocks & Files

Qdrant launches pure vector-based hybrid search for more accurate AI data retrieval
2 July 2024, SiliconANGLE News

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

Vector database company Qdrant wants RAG to be more cost-effective
2 July 2024, VentureBeat

provided by Google News



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