DBMS > Apache Phoenix vs. Dgraph vs. NuoDB vs. RocksDB vs. YugabyteDB

System Properties Comparison Apache Phoenix vs. Dgraph vs. NuoDB vs. RocksDB vs. YugabyteDB

Editorial information provided by DB-Engines

Name

Description

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

Distributed and scalable native Graph DBMS

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

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

High-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL.

Primary database model

Secondary database models

Document store
Wide column store

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

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	2.91
Rank	#102	Overall
	#51	Relational DBMS

Website

phoenix.apache.org

dgraph.io

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

rocksdb.org

www.yugabyte.com

Technical documentation

phoenix.apache.org

dgraph.io/docs

doc.nuodb.com

github.com/facebook/rocksdb/wiki

docs.yugabyte.com
github.com/yugabyte/yugabyte-db

Developer

Apache Software Foundation

Dgraph Labs, Inc.

Dassault Systèmes

originally NuoDB, Inc.

Facebook, Inc.

Yugabyte Inc.

Initial release

2014

2016

2013

2017

Current release

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

8.11.4, April 2024

2.19, September 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

limited edition free

Open Source

BSD

Open Source

Apache 2.0

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.

YugabyteDB Managed is the fully managed database-as-a-service offering of YugabyteDB. Get started quickly, and effortlessly ensure continuous availability and limitless scale of your cloud native applications.

Implementation language

Java

C++

C and C++

Server operating systems

Linux
Unix
Windows

Linux
OS X
Windows

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Linux

Linux
OS X

Data scheme

yes

late-bound, schema-on-read capabilities

schema-free

yes

schema-free

depending on used data model

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

SQL

Support of SQL

yes

yes, PostgreSQL compatible

APIs and other access methods

JDBC

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

ADO.NET
JDBC
ODBC

C++ API
Java API

JDBC
YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language
YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL

Supported programming languages

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

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

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

C
C++
Go
Java
Perl
Python
Ruby

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

Server-side scripts

Stored procedures

user defined functions

Java, SQL

yes

sql, plpgsql, C

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

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

horizontal partitioning

Hash and Range Sharding, row-level geo-partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Synchronous replication via Raft

yes

Managed transparently by NuoDB

yes

Based on Raft distributed consensus protocol, minimum 3 replicas for continuous availability

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency

Strong consistency on writes and tunable consistency on reads

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

tunable commit protocol

yes

Distributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture.

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

Durability

Support for making data persistent

yes

based on RocksDB

In-memory capabilities

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

yes

Temporary table

yes

User concepts

Access control

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

Planned for future releases

Standard SQL roles/ privileges, Administrative Users

yes

More information provided by the system vendor

Specific characteristics

YugabyteDB is an open source distributed SQL database for cloud native transactional...
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Competitive advantages

PostgreSQL compatible: Get instantly productive with a PostgreSQL compatible RDBMS....
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Typical application scenarios

Systems of record and engagement for cloud native applications that require resilience,...
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Market metrics

2 Million+ lifetime clusters deployed, 6.5K+ GitHub stars, 7K YugabyteDB Community...
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Licensing and pricing models

Apache 2.0 license for the database
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