DBMS > Dragonfly vs. HEAVY.AI vs. Heroic vs. LokiJS

System Properties Comparison Dragonfly vs. HEAVY.AI vs. Heroic vs. LokiJS

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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

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

In-memory JavaScript DBMS

Primary database model

Secondary database models

Spatial DBMS

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

Score	0.41
Rank	#266	Overall
	#38	Key-value stores

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	0.43
Rank	#264	Overall
	#42	Document stores

Website

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

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

github.com/spotify/heroic

github.com/techfort/LokiJS

Technical documentation

www.dragonflydb.io/docs

docs.heavy.ai

spotify.github.io/heroic

techfort.github.io/LokiJS

Developer

DragonflyDB team and community contributors

HEAVY.AI, Inc.

Spotify

Initial release

2023

2016

2014

Current release

1.0, March 2023

5.10, January 2022

License

Commercial or Open Source

Open Source

BSL 1.1

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache 2.0

Open Source

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

C++ and CUDA

Java

JavaScript

Server operating systems

Linux

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

Data scheme

scheme-free

yes

schema-free

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.

Secondary indexes

yes

via Elasticsearch

yes

via views

SQL

Support of SQL

yes

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

JDBC
ODBC
Thrift
Vega

HQL (Heroic Query Language, a JSON-based language)
HTTP API

JavaScript API

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

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript

Server-side scripts

Stored procedures

Lua

View functions in JavaScript

Triggers

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

none

Foreign keys

Referential integrity

Transaction concepts

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

Atomic execution of command blocks and scripts

atomic operations within a single collection possible

Concurrency

Support for concurrent manipulation of data

yes, strict serializability by the server

yes

Durability

Support for making data persistent

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

In-memory capabilities

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

yes

User concepts

Access control

Password-based authentication

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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