DBMS > Coveo vs. Dragonfly vs. HEAVY.AI vs. Snowflake

System Properties Comparison Coveo vs. Dragonfly vs. HEAVY.AI vs. Snowflake

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

AI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code development

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Search engine

Key-value store

Relational DBMS

Secondary database models

Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	2.11
Rank	#118	Overall
	#11	Search engines

Score	0.49
Rank	#261	Overall
	#38	Key-value stores

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

www.coveo.com

github.com/dragonflydb/dragonfly
www.dragonflydb.io

github.com/heavyai/heavydb
www.heavy.ai

www.snowflake.com

Technical documentation

docs.coveo.com

www.dragonflydb.io/docs

docs.heavy.ai

docs.snowflake.net/manuals/index.html

Developer

Coveo

DragonflyDB team and community contributors

HEAVY.AI, Inc.

Snowflake Computing Inc.

Initial release

2012

2023

2016

2014

Current release

1.0, March 2023

5.10, January 2022

License

Commercial or Open Source

commercial

Open Source

BSL 1.1

Open Source

Apache Version 2; enterprise edition available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

C++ and CUDA

Server operating systems

hosted

Linux

hosted

Data scheme

hybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configuration

scheme-free

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

strings, hashes, lists, sets, sorted sets, bit arrays

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP API

Proprietary protocol

RESP - REdis Serialization Protocol

JDBC
ODBC
Thrift
Vega

CLI Client
JDBC
ODBC

Supported programming languages

C#
Java
JavaScript
Python

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Lua

user defined functions

Triggers

yes

publish/subscribe channels provide some trigger functionality

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

Round robin

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

yes

Atomic execution of command blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

granular access controls, API key management, content filters

Password-based authentication

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles and pluggable authentication

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.