DBMS > Amazon DynamoDB vs. Apache Phoenix vs. NebulaGraph vs. Oracle Coherence vs. Spark SQL

System Properties Comparison Amazon DynamoDB vs. Apache Phoenix vs. NebulaGraph vs. Oracle Coherence vs. Spark SQL

Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

A scale-out RDBMS with evolutionary schema built on Apache HBase

A distributed, linear scalable, high perfomant Graph DBMS

Oracles in-memory data grid solution

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Document store
Key-value store

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

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	2.14
Rank	#120	Overall
	#10	Graph DBMS

Score	1.92
Rank	#130	Overall
	#22	Key-value stores

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

aws.amazon.com/dynamodb

phoenix.apache.org

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

www.oracle.com/java/coherence

spark.apache.org/sql

Technical documentation

docs.aws.amazon.com/dynamodb

phoenix.apache.org

docs.nebula-graph.io

docs.oracle.com/en/middleware/standalone/coherence

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Amazon

Apache Software Foundation

Vesoft Inc.

Oracle

Apache Software Foundation

Initial release

2012

2014

2019

2007

2014

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

14.1, August 2023

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0 + Common Clause 1.0

commercial

Open Source

Apache 2.0

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++

Java

Scala

Server operating systems

hosted

Linux
Unix
Windows

Linux

All OS with a Java VM

Linux
OS X
Windows

Data scheme

schema-free

yes

late-bound, schema-on-read capabilities

Strong typed schema

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

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

SQL-like query language

SQL-like DML and DDL statements

APIs and other access methods

RESTful HTTP API

JDBC

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

JCache
JPA
RESTful HTTP API

JDBC
ODBC

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

.Net
C++
Go
Java
PHP
Python

.Net
C++
Java

Java
Python
R
Scala

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

by integration with AWS Lambda

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

Causal Clustering using Raft protocol

yes, with selectable consistency level

none

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency or Eventual Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

ACID

configurable

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using RocksDB

yes

optionally

yes

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

Role-based access control

authentification to access the cache via certificates or http basic authentication

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...
» more

Licensing and pricing models

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

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