DBMS > atoti vs. Google BigQuery vs. NebulaGraph vs. ScyllaDB

System Properties Comparison atoti vs. Google BigQuery vs. NebulaGraph vs. ScyllaDB

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Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

Large scale data warehouse service with append-only tables

A distributed, linear scalable, high perfomant Graph DBMS

Cassandra and DynamoDB compatible wide column store

Primary database model

Secondary database models

Key-value store

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

Score	0.45
Rank	#253	Overall
	#13	Object oriented DBMS

Score	52.67
Rank	#19	Overall
	#13	Relational DBMS

Score	1.92
Rank	#122	Overall
	#11	Graph DBMS

Score	4.15
Rank	#69	Overall
	#5	Wide column stores

Website

atoti.io

cloud.google.com/bigquery

github.com/vesoft-inc/nebula
www.nebula-graph.io

www.scylladb.com

Technical documentation

docs.atoti.io

cloud.google.com/bigquery/docs

docs.nebula-graph.io

docs.scylladb.com

Developer

ActiveViam

Google

Vesoft Inc.

ScyllaDB

Initial release

2010

2019

2015

Current release

ScyllaDB Open Source 6.0.2, July 2024

License

Commercial or Open Source

commercial

free versions available

commercial

Open Source

Apache Version 2.0 + Common Clause 1.0

Open Source

Open Source (AGPL), commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

hosted

Linux

Data scheme

yes

Strong typed schema

schema-free

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

Nebula Graph internally uses the Key-Value store RocksDB for persistency. The vertices, edges, and their properties are stored as Key while their values are stored as Value. The primary indexes are per Key and secondary indexes are per Value.

yes

cluster global secondary indices

SQL

Support of SQL

Multidimensional Expressions (MDX)

yes

SQL-like query language

SQL-like DML and DDL statements (CQL)

APIs and other access methods

RESTful HTTP/JSON API

Browser interface
console (shell)
Cypher Query Language
GO Object Graph Mapper
Java Object Graph Mapper
NGBatis

ORM framework for NebulaGraph and Spring-Boot
Proprietary native API
Python Object Graph Mapper
Query language nGQL

Proprietary protocol (CQL)

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

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C++
Go
Java
PHP
Python

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

Python

user defined functions

in JavaScript

user defined functions

yes, Lua

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Causal Clustering using Raft protocol

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

Immediate Consistency

Eventual Consistency
Tunable Consistency

can be individually decided for each write operation

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

Atomicity and isolation are supported for single operations

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

using RocksDB

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

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Role-based access control

Access rights for users can be defined per object

More information provided by the system vendor

Specific characteristics

NebulaGraph is a truly distributed, linearly scalable, lightning-fast graph database,...
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ScyllaDB is engineered to deliver predictable performance at scale. It’s adopted...
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Competitive advantages

NebulaGraph boasts the world's only graph database solution that is able to host...
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Highly-performant (efficiently utilizes full resources of a node and network; millions...
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Typical application scenarios

Social networking Fraud detection Knowledge graph Data warehouse management Anti...
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ScyllaDB is ideal for applications that require high throughput and low latency at...
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Key customers

Companies from a variety of industries have implemented NebulaGraph Database in production,...
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Discord, Epic Games, Expedia, Zillow, Comcast, Disney+ Hotstar, Samsung, ShareChat,...
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Market metrics

At our very early stage, NebulaGraph has already received over 10,000 stars on GitHub...
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ScyllaDB typically offers ~75% total cost of ownership savings, with ~5X higher throughput...
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Licensing and pricing models

NebulaGraph is open source and free to use under Apache 2.0 license.
» more

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

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