DBMS > Dragonfly vs. KairosDB vs. Kinetica vs. Lovefield vs. Snowflake

System Properties Comparison Dragonfly vs. KairosDB vs. Kinetica vs. Lovefield vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

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

Distributed Time Series DBMS based on Cassandra or H2

Fully vectorized database across both GPUs and CPUs

Embeddable relational database for web apps written in pure JavaScript

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

Primary database model

Key-value store

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

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

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

Score	0.67
Rank	#233	Overall
	#20	Time Series DBMS

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

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

github.com/kairosdb/kairosdb

www.kinetica.com

google.github.io/lovefield

www.snowflake.com

Technical documentation

www.dragonflydb.io/docs

kairosdb.github.io

docs.kinetica.com

github.com/google/lovefield/blob/master/docs/spec_index.md

docs.snowflake.net/manuals/index.html

Developer

DragonflyDB team and community contributors

Kinetica

Google

Snowflake Computing Inc.

Initial release

2023

2013

2012

2014

Current release

1.0, March 2023

1.2.2, November 2018

7.1, August 2021

2.1.12, February 2017

License

Commercial or Open Source

Open Source

BSL 1.1

Open Source

Apache 2.0

commercial

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

C, C++

JavaScript

Server operating systems

Linux

Linux
OS X
Windows

Linux

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

hosted

Data scheme

scheme-free

schema-free

yes

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

Typing

predefined data types such as float or date

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

SQL-like DML and DDL statements

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

Graphite protocol
HTTP REST
Telnet API

JDBC
ODBC
RESTful HTTP API

CLI Client
JDBC
ODBC

Supported programming languages

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

Java
JavaScript

Node.js
PHP
Python

C++
Java
JavaScript (Node.js)
Python

JavaScript

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Lua

user defined functions

Triggers

publish/subscribe channels provide some trigger functionality

yes

triggers when inserted values for one or more columns fall within a specified range

Using read-only observers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

based on Cassandra

Source-replica replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of command blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes, strict serializability by the server

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

GPU vRAM or System RAM

yes

using MemoryDB

User concepts

Access control

Password-based authentication

simple password-based access control

Access rights for users and roles on table level

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

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