DBMS > Bangdb vs. Dgraph vs. EJDB vs. RDFox vs. ScyllaDB

System Properties Comparison Bangdb vs. Dgraph vs. EJDB vs. RDFox vs. ScyllaDB

Editorial information provided by DB-Engines

Name

Description

Converged and high performance database for device data, events, time series, document and graph

Distributed and scalable native Graph DBMS

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

High performance knowledge graph and semantic reasoning engine

Cassandra and DynamoDB compatible wide column store

Primary database model

Document store
Graph DBMS
Time Series DBMS

Secondary database models

Spatial DBMS

Relational DBMS

Key-value store

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

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	0.23
Rank	#308	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	4.75
Rank	#68	Overall
	#5	Wide column stores

Website

bangdb.com

dgraph.io

github.com/Softmotions/ejdb

www.oxfordsemantic.tech

www.scylladb.com

Technical documentation

docs.bangdb.com

dgraph.io/docs

github.com/Softmotions/ejdb/blob/master/README.md

docs.oxfordsemantic.tech

docs.scylladb.com

Developer

Sachin Sinha, BangDB

Dgraph Labs, Inc.

Softmotions

Oxford Semantic Technologies

ScyllaDB

Initial release

2012

2016

2012

2017

2015

Current release

BangDB 2.0, October 2021

6.0, Septermber 2022

ScyllaDB Open Source 5.4.1, January 2024

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Apache 2.0

Open Source

GPLv2

commercial

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

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Implementation language

C, C++

C++

Server operating systems

Linux

Linux
OS X
Windows

server-less

Linux
macOS
Windows

Linux

Data scheme

schema-free

yes

RDF schemas

schema-free

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

yes

string, integer, double, bool, date, object_id

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

secondary, composite, nested, reverse, geospatial

yes

cluster global secondary indices

SQL

Support of SQL

SQL like support with command line tool

SQL-like DML and DDL statements (CQL)

APIs and other access methods

Proprietary protocol
RESTful HTTP API

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

in-process shared library

RESTful HTTP API
SPARQL 1.1

Proprietary protocol (CQL)

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

Supported programming languages

C
C#
C++
Java
Python

C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

C
Java

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, Lua

Triggers

yes, Notifications (with Streaming only)

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

yes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

Synchronous replication via Raft

none

replication via a shared file system

selectable replication factor

Representation of geographical distribution of servers is possible

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

Eventual Consistency
Tunable Consistency

can be individually decided for each write operation

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

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, optimistic concurrency control

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

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

yes, run db with in-memory only mode

yes

in-memory tables

User concepts

Access control

yes (enterprise version only)

Planned for future releases

Roles, resources, and access types

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...
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Typical application scenarios

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

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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