DBMS > Dragonfly vs. Hyprcubd vs. Infobright vs. ObjectBox vs. Splice Machine

System Properties Comparison Dragonfly vs. Hyprcubd vs. Infobright vs. ObjectBox vs. Splice Machine

Editorial information provided by DB-Engines

Name

Hyprcubd seems to be discontinued. Therefore it is excluded 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

Serverless Time Series DBMS

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Extremely fast embedded database for small devices, IoT and Mobile

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Secondary database models

Time Series DBMS

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

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

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	1.20
Rank	#170	Overall
	#5	Object oriented DBMS

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Website

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

hyprcubd.com (offline)

ignitetech.com/softwarelibrary/infobrightdb

objectbox.io

splicemachine.com

Technical documentation

www.dragonflydb.io/docs

docs.objectbox.io

splicemachine.com/how-it-works

Developer

DragonflyDB team and community contributors

Hyprcubd, Inc.

Ignite Technologies Inc.; formerly InfoBright Inc.

ObjectBox Limited

Splice Machine

Initial release

2023

2005

2017

2014

Current release

1.0, March 2023

3.1, March 2021

License

Commercial or Open Source

Open Source

BSL 1.1

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

Apache License 2.0

Open Source

AGPL 3.0, commercial license available

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 C++

Java

Server operating systems

Linux

hosted

Linux
Windows

Android
iOS
Linux
macOS
Windows

Linux
OS X
Solaris
Windows

Data scheme

scheme-free

yes

Typing

predefined data types such as float or date

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

yes

time, int, uint, float, string

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

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

gRPC (https)

ADO.NET
JDBC
ODBC

Proprietary native API

JDBC
Native Spark Datasource
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

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

Lua

yes

Java

Triggers

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

none

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

online/offline synchronization between client and server

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

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

yes, multi-version concurrency control (MVCC)

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

token access

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

yes

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

More information provided by the system vendor

News

On-device Vector Database for Dart/Flutter
21 May 2024

The first On-Device Vector Database: ObjectBox 4.0
16 May 2024

Edge AI: The era of on-device AI
23 April 2024

In-Memory Database Use Cases
15 February 2024

Data Viewer for Objects – announcing ObjectBox Admin
14 November 2023

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