DBMS > Dragonfly vs. Hazelcast vs. Snowflake vs. Sqrrl vs. UniData,UniVerse

System Properties Comparison Dragonfly vs. Hazelcast vs. Snowflake vs. Sqrrl vs. UniData,UniVerse

Editorial information provided by DB-Engines

Name

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.

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 widely adopted in-memory data grid

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

Adaptable, secure NoSQL built on Apache Accumulo

MultiValue database and application server with SQL mapping layer and meta database capabilities

Primary database model

Key-value store

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Multivalue DBMS

Secondary database models

Document store

JSON support with IMDG 3.12

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

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

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	3.16
Rank	#97	Overall
	#2	Multivalue DBMS

Website

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

hazelcast.com

www.snowflake.com

sqrrl.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

Technical documentation

www.dragonflydb.io/docs

hazelcast.org/imdg/docs

docs.snowflake.net/manuals/index.html

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

DragonflyDB team and community contributors

Hazelcast

Snowflake Computing Inc.

Amazon

originally Sqrrl Data, Inc.

Rocket Software

Initial release

2023

2008

2014

2012

1985

Current release

1.0, March 2023

5.3.6, November 2023

License

Commercial or Open Source

Open Source

BSL 1.1

Open Source

Apache Version 2; commercial licenses 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++

Java

Server operating systems

Linux

All OS with a Java VM

hosted

Linux

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

scheme-free

schema-free

yes

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

schema-free

Typing

predefined data types such as float or date

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

yes

optional

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

the object must implement a serialization strategy

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

JCache
JPA
Memcached protocol
RESTful HTTP API

CLI Client
JDBC
ODBC

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based 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

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

JavaScript (Node.js)
Python

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

Lua

yes

Event Listeners, Executor Services

user defined functions

yes

Triggers

publish/subscribe channels provide some trigger functionality

yes

Events

similar concept for controling cloud resources

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

making use of Hadoop

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Replicated Map

yes

selectable replication factor

making use of Hadoop

Source-replica replication

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 or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

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

one or two-phase-commit; repeatable reads; read commited

ACID

Atomic updates per row, document, or graph entity

ACID

configurable

Concurrency

Support for concurrent manipulation of data

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

Password-based authentication

Role-based access control

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

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

Access rights according to SQL-standard and operating system based

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