DBMS > Amazon Redshift vs. Coveo vs. Google Cloud Spanner vs. Hive vs. NebulaGraph

System Properties Comparison Amazon Redshift vs. Coveo vs. Google Cloud Spanner vs. Hive vs. NebulaGraph

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

AI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code development

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

data warehouse software for querying and managing large distributed datasets, built on Hadoop

A distributed, linear scalable, high perfomant Graph DBMS

Primary database model

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	2.11
Rank	#118	Overall
	#11	Search engines

Score	2.84
Rank	#100	Overall
	#51	Relational DBMS

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	2.23
Rank	#116	Overall
	#10	Graph DBMS

Website

aws.amazon.com/redshift

www.coveo.com

cloud.google.com/spanner

hive.apache.org

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

Technical documentation

docs.aws.amazon.com/redshift

docs.coveo.com

cloud.google.com/spanner/docs

cwiki.apache.org/confluence/display/Hive/Home

docs.nebula-graph.io

Developer

Amazon (based on PostgreSQL)

Coveo

Google

Apache Software Foundation

initially developed by Facebook

Vesoft Inc.

Initial release

2012

2017

2012

2019

Current release

3.1.3, April 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

Apache Version 2.0 + Common Clause 1.0

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

Java

C++

Server operating systems

hosted

All OS with a Java VM

Linux

Data scheme

yes

hybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configuration

yes

Strong typed schema

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

restricted

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.

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

Query statements complying to ANSI 2011

SQL-like DML and DDL statements

SQL-like query language

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

JDBC
ODBC
Thrift

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

Supported programming languages

All languages supporting JDBC/ODBC

C#
Java
JavaScript
Python

Go
Java
JavaScript (Node.js)
Python

C++
Java
PHP
Python

.Net
C++
Go
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in Python

yes

user defined functions and integration of map-reduce

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication with 3 replicas for regional instances.

selectable replication factor

Causal Clustering using Raft protocol

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

yes

ACID

Strict serializable isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using RocksDB

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

granular access controls, API key management, content filters

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Access rights for users, groups and roles

Role-based access control

More information provided by the system vendor

Specific characteristics

NebulaGraph is a truly distributed, linearly scalable, lightning-fast graph database,...
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Competitive advantages

NebulaGraph boasts the world's only graph database solution that is able to host...
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Typical application scenarios

Social networking Fraud detection Knowledge graph Data warehouse management Anti...
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Key customers

Companies from a variety of industries have implemented NebulaGraph Database in production,...
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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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Licensing and pricing models

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