DBMS > Apache Phoenix vs. HugeGraph vs. Ingres vs. Oracle vs. YDB

System Properties Comparison Apache Phoenix vs. HugeGraph vs. Ingres vs. Oracle vs. YDB

Editorial information provided by DB-Engines

Name

Description

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

A fast-speed and highly-scalable Graph DBMS

Well established RDBMS

Widely used RDBMS

A distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API

Primary database model

Relational DBMS

Graph DBMS

Relational DBMS

Document store
Relational DBMS

Secondary database models

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	4.11
Rank	#81	Overall
	#44	Relational DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	0.35
Rank	#278	Overall
	#43	Document stores
	#127	Relational DBMS

Website

phoenix.apache.org

github.com/hugegraph
hugegraph.apache.org

www.actian.com/databases/ingres

www.oracle.com/database

github.com/ydb-platform/ydb
ydb.tech

Technical documentation

phoenix.apache.org

hugegraph.apache.org/docs

docs.actian.com/ingres

docs.oracle.com/en/database

ydb.tech/en/docs

Developer

Apache Software Foundation

Baidu

Actian Corporation

Oracle

Yandex

Initial release

2014

2018

1974

originally developed at University Berkely in early 1970s

1980

2019

Current release

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

0.9

11.2, May 2022

23c, September 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

commercial

restricted free version is available

Open Source

Apache 2.0; commercial license available

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.

Implementation language

Java

C and C++

Server operating systems

Linux
Unix
Windows

Linux
macOS
Unix

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Linux

Data scheme

yes

late-bound, schema-on-read capabilities

yes

Schemaless in JSON and XML columns

Flexible Schema (defined schema, partial 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.

but tools for importing/exporting data from/to XML-files available

yes

Secondary indexes

yes

also supports composite index and range index

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-like query language (YQL)

APIs and other access methods

JDBC

Java API
RESTful HTTP API
TinkerPop Gremlin

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

RESTful HTTP API (DynamoDB compatible)

Supported programming languages

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

Groovy
Java
Python

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Go
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

user defined functions

asynchronous Gremlin script jobs

yes

PL/SQL

also stored procedures in Java possible

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

depending on used storage backend, e.g. Cassandra and HBase

horizontal partitioning

Ingres Star to access multiple databases simultaneously

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

depending on used storage backend, e.g. Cassandra and HBase

Ingres Replicator

Multi-source replication
Source-replica replication

Active-passive shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

via hugegraph-spark

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

Transaction concepts

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

ACID

isolation level can be parameterized

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

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

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

Users, roles and permissions

fine grained access rights according to SQL-standard

Access rights defined for Yandex Cloud users

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