DBMS > BigObject vs. Dragonfly vs. InfinityDB vs. openGauss

System Properties Comparison BigObject vs. Dragonfly vs. InfinityDB vs. openGauss

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

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 Java embedded Key-Value Store which extends the Java Map interface

An enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by Huawei

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Key-value store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

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

Score	0.00
Rank	#378	Overall
	#57	Key-value stores

Score	1.08
Rank	#183	Overall
	#84	Relational DBMS

Website

bigobject.io

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

boilerbay.com

gitee.com/opengauss
opengauss.org

Technical documentation

docs.bigobject.io

www.dragonflydb.io/docs

boilerbay.com/infinitydb/manual

docs.opengauss.org/en
gitee.com/opengauss/docs

Developer

BigObject, Inc.

DragonflyDB team and community contributors

Boiler Bay Inc.

Huawei and openGauss community

Initial release

2015

2023

2002

2019

Current release

1.0, March 2023

4.0

3.0, March 2022

License

Commercial or Open Source

commercial

free community edition available

Open Source

BSL 1.1

commercial

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++

Java

C, C++, Java

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux

All OS with a Java VM

Linux

Data scheme

yes

scheme-free

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

yes

Typing

predefined data types such as float or date

yes

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

yes

all Java primitives, Date, CLOB, BLOB, huge sparse 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

manual creation possible, using inversions based on multi-value capability

yes

SQL

Support of SQL

SQL-like DML and DDL statements

ANSI SQL 2011

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

Proprietary protocol

RESP - REdis Serialization Protocol

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

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

C
C++
Java

Server-side scripts

Stored procedures

Lua

yes

Triggers

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning (by range, list and hash)

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Immediate Consistency

READ-COMMITTED or SERIALIZED

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

manual creation possible, using inversions based on multi-value capability

yes

Transaction concepts

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

Atomic execution of command blocks and scripts

ACID

Optimistic locking for transactions; no isolation for bulk loads

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

Access rights for users, groups and roles according to SQL-standard

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More resources

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