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DBMS > HEAVY.AI vs. NCache vs. Qdrant

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

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Editorial information provided by DB-Engines
NameHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonNCache  Xexclude from comparisonQdrant  Xexclude from comparison
DescriptionA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareOpen-Source and Enterprise in-memory Key-Value StoreA high-performance vector database with neural network or semantic-based matching
Primary database modelRelational DBMSKey-value storeVector DBMS
Secondary database modelsSpatial DBMSDocument store
Search engine infoUsing distributed Lucene
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.25
Rank#161  Overall
#72  Relational DBMS
Score0.90
Rank#198  Overall
#31  Key-value stores
Score1.94
Rank#118  Overall
#8  Vector DBMS
Websitegithub.com/­heavyai/­heavydb
www.heavy.ai
www.alachisoft.com/­ncachegithub.com/­qdrant/­qdrant
qdrant.tech
Technical documentationdocs.heavy.aiwww.alachisoft.com/­resources/­docsqdrant.tech/­documentation
DeveloperHEAVY.AI, Inc.AlachisoftQdrant
Initial release201620052021
Current release5.10, January 20225.3.3, April 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2; enterprise edition availableOpen Source infoEnterprise 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++ and CUDAC#, .NET, .NET Core, JavaRust
Server operating systemsLinuxLinux
Windows
Docker
Linux
macOS
Windows
Data schemeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyespartial infoSupported data types are Lists, Queues, Hashsets, Dictionary and CounterNumbers, 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 indexesnoyesyes infoKeywords, numberic ranges, geo, full-text
SQL infoSupport of SQLyesSQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.no
APIs and other access methodsJDBC
ODBC
Thrift
Vega
IDistributedCache
JCache
LINQ
Proprietary native API
gRPC
OpenAPI 3.0
RESTful HTTP/JSON API infoOpenAPI 3.0
Supported programming languagesAll languages supporting JDBC/ODBC/Thrift
Python
.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
Python
Rust
Server-side scripts infoStored proceduresnono infosupport for stored procedures with SQL-Server CLR
Triggersnoyes infoNotifications
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinyesSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyes, with selectable consistency levelCollection-level replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology
Eventual Consistency, tunable consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanooptimistic locking and pessimistic locking
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.yesyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAuthentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)Key-based authentication
More information provided by the system vendor
HEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022NCacheQdrant
Specific characteristicsNCache has been the market leader in .NET Distributed Caching since 2005 . NCache...
» more
Competitive advantagesNCache is 100% .NET/ .NET Core based which fully supports ASP.NET Core Sessions ,...
» more
Typical application scenariosNCache enables industries like retail, finance, banking IoT, travel, ecommerce, healthcare...
» more
Key customersBank of America, Citi, Natures Way, Charter Spectrum, Barclays, Henry Schein, GBM,...
» more
Market metricsMarket Leader in .NET Distributed Caching since 2005.
» more
Licensing and pricing modelsNCache Open Source is free on an as-is basis without any support. NCache Enterprise...
» more

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

HEAVY.AI Announces Availability of Analytics Platform Accelerated by NVIDIA Grace Hopper Superchip
21 January 2025, Business Wire

5 Q’s for Mike Flaxman, Vice President of Heavy.AI
15 August 2024, Center for Data Innovation

HEAVY.AI Launches Analytics Platform Optimized for NVIDIA Grace Hopper Superchip
21 January 2025, SDxCentral

HEAVY.AI Accelerates Big Data Analytics with Vultr's High-Performance GPU Cloud Infrastructure
11 September 2024, Inside AI News

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

provided by Google News

How to use NCache in ASP.Net Core
9 July 2024, InfoWorld

Custom Response Caching Using NCache in ASP.NET Core
22 April 2020, InfoQ.com

provided by Google News

Qdrant Launches the First Platform-Independent GPU-Accelerated Vector Indexing for Real-Time AI Applications
23 January 2025, Business Wire

Qdrant promises 10x faster indexing with GPU-powered vector database
23 January 2025, Blocks and Files

Qdrant launches hardware-independent, GPU-accelerated vector indexing capability
23 January 2025, SiliconANGLE News

Qdrant review: A highly flexible option for vector search
29 July 2024, InfoWorld

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

provided by Google News



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