DBMS > Dgraph vs. JaguarDB vs. NuoDB vs. ScyllaDB vs. Yaacomo

System Properties Comparison Dgraph vs. JaguarDB vs. NuoDB vs. ScyllaDB vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

Distributed and scalable native Graph DBMS

Performant, highly scalable DBMS for AI and IoT applications

NuoDB is a webscale distributed database that supports SQL and ACID transactions

Cassandra and DynamoDB compatible wide column store

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Graph DBMS

Key-value store
Vector DBMS

Relational DBMS

Wide column store

Relational DBMS

Secondary database models

Key-value store

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

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

Score	4.75
Rank	#68	Overall
	#5	Wide column stores

Website

dgraph.io

www.jaguardb.com

www.3ds.com/nuodb-distributed-sql-database

www.scylladb.com

yaacomo.com

Technical documentation

dgraph.io/docs

www.jaguardb.com/support.html

doc.nuodb.com

docs.scylladb.com

Developer

Dgraph Labs, Inc.

DataJaguar, Inc.

Dassault Systèmes

originally NuoDB, Inc.

ScyllaDB

Q2WEB GmbH

Initial release

2016

2015

2013

2015

2009

Current release

3.3 July 2023

ScyllaDB Open Source 5.4.1, January 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPL V3.0

commercial

limited edition free

Open Source

Open Source (AGPL), commercial license available

commercial

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

C++

the server part. Clients available in other languages

C++

Server operating systems

Linux
OS X
Windows

Linux

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Linux

Android
Linux
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

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

cluster global secondary indices

yes

SQL

Support of SQL

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

SQL-like DML and DDL statements (CQL)

yes

APIs and other access methods

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

JDBC
ODBC

ADO.NET
JDBC
ODBC

Proprietary protocol (CQL)

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

JDBC
ODBC

Supported programming languages

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

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

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

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

Java, SQL

yes, Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

data is dynamically stored/cached on the nodes where it is read/written

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

Multi-source replication

yes

Managed transparently by NuoDB

selectable replication factor

Representation of geographical distribution of servers is possible

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Eventual Consistency
Tunable Consistency

can be individually decided for each write operation

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

tunable commit protocol

Atomicity and isolation are supported for single operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

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

Temporary table

yes

in-memory tables

yes

User concepts

Access control

Planned for future releases

rights management via user accounts

Standard SQL roles/ privileges, Administrative Users

Access rights for users can be defined per object

fine grained access rights according to SQL-standard

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

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

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