DBMS > 4D vs. Graphite vs. HugeGraph vs. ObjectBox vs. ScyllaDB

System Properties Comparison 4D vs. Graphite vs. HugeGraph vs. ObjectBox vs. ScyllaDB

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

A fast-speed and highly-scalable Graph DBMS

Extremely fast embedded database for small devices, IoT and Mobile

Cassandra and DynamoDB compatible wide column store

Primary database model

Secondary database models

Time Series DBMS

Key-value store

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	4.57
Rank	#73	Overall
	#5	Time Series DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	1.20
Rank	#170	Overall
	#5	Object oriented DBMS

Score	4.75
Rank	#68	Overall
	#5	Wide column stores

Website

www.4d.com

github.com/graphite-project/graphite-web

github.com/hugegraph
hugegraph.apache.org

objectbox.io

www.scylladb.com

Technical documentation

developer.4d.com

graphite.readthedocs.io

hugegraph.apache.org/docs

docs.objectbox.io

docs.scylladb.com

Developer

4D, Inc

Chris Davis

Baidu

ObjectBox Limited

ScyllaDB

Initial release

1984

2006

2018

2017

2015

Current release

v20, April 2023

0.9

ScyllaDB Open Source 5.4.1, January 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Open Source

Apache License 2.0

Open Source

Open Source (AGPL), commercial license available

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.

Scylla Cloud: Create real-time applications that run at global scale with Scylla Cloud, the industry’s most powerful NoSQL DBaaS

Implementation language

Python

Java

C and C++

C++

Server operating systems

OS X
Windows

Linux
Unix

Linux
macOS
Unix

Android
iOS
Linux
macOS
Windows

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data only

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

also supports composite index and range index

yes

cluster global secondary indices

SQL

Support of SQL

yes

close to SQL 92

SQL-like DML and DDL statements (CQL)

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

HTTP API
Sockets

Java API
RESTful HTTP API
TinkerPop Gremlin

Proprietary native API

Proprietary protocol (CQL)

compatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift

Supported programming languages

4D proprietary IDE
PHP

JavaScript (Node.js)
Python

Groovy
Java
Python

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

For CQL interface: C#, C++, Clojure, Erlang, Go, Haskell, Java, JavaScript, Node.js, Perl, PHP, Python, Ruby, Rust, Scala
For DynamoDB interface: .Net, ColdFusion, Erlang, Groovy, Java, JavaScript, Perl, PHP, Python, Ruby

Server-side scripts

Stored procedures

yes

asynchronous Gremlin script jobs

yes, Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

depending on used storage backend, e.g. Cassandra and HBase

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

yes

depending on used storage backend, e.g. Cassandra and HBase

online/offline synchronization between client and server

selectable replication factor

Representation of geographical distribution of servers is possible

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Eventual Consistency

Immediate Consistency

Eventual Consistency
Tunable Consistency

can be individually decided for each write operation

Foreign keys

Referential integrity

yes

edges in graph

yes

Transaction concepts

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

ACID

Atomicity and isolation are supported for single operations

Concurrency

Support for concurrent manipulation of data

yes

locking

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

in-memory tables

User concepts

Access control

Users and groups

Users, roles and permissions

yes

Access rights for users can be defined per object

More information provided by the system vendor

Specific characteristics

ScyllaDB is engineered to deliver predictable performance at scale. It’s adopted...
» more

Competitive advantages

Highly-performant (efficiently utilizes full resources of a node and network; millions...
» more

Typical application scenarios

ScyllaDB is ideal for applications that require high throughput and low latency at...
» more

Key customers

Discord, Epic Games, Expedia, Zillow, Comcast, Disney+ Hotstar, Samsung, ShareChat,...
» more

Market metrics

ScyllaDB typically offers ~75% total cost of ownership savings, with ~5X higher throughput...
» more

Licensing and pricing models

ScyllaDB Open Source - free open source software (AGPL) ScyllaDB Enterprise - subscription-based...
» more

News

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

Vector Databases for Edge AI
9 August 2023

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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More resources

DB-Engines blog posts

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

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Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

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Recent citations in the news

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10 December 2018, Uber

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ScyllaDB on AWS is a NoSQL Database Built for Gigabyte-to-Petabyte Scale | Amazon Web Services
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