DBMS > Apache Phoenix vs. ArcadeDB vs. DolphinDB vs. Ingres

System Properties Comparison Apache Phoenix vs. ArcadeDB vs. DolphinDB vs. Ingres

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Editorial information provided by DB-Engines

Name

Description

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

Fast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewritten

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

Well established RDBMS

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Time Series DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	2.06
Rank	#123	Overall
	#58	Relational DBMS

Score	0.10
Rank	#358	Overall
	#48	Document stores
	#38	Graph DBMS
	#52	Key-value stores
	#35	Time Series DBMS

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	3.80
Rank	#82	Overall
	#44	Relational DBMS

Website

phoenix.apache.org

arcadedb.com

www.dolphindb.com

www.actian.com/databases/ingres

Technical documentation

phoenix.apache.org

docs.arcadedb.com

docs.dolphindb.cn/en/help200/index.html

docs.actian.com/ingres

Developer

Apache Software Foundation

Arcade Data

DolphinDB, Inc

Actian Corporation

Initial release

2014

2021

2018

1974

originally developed at University Berkely in early 1970s

Current release

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

September 2021

v2.00.4, January 2022

11.2, May 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

commercial

free community version available

commercial

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++

Server operating systems

Linux
Unix
Windows

All OS with a Java VM

Linux
Windows

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Data scheme

yes

late-bound, schema-on-read capabilities

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.

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

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language, no joins

SQL-like query language

yes

APIs and other access methods

JDBC

JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

Supported programming languages

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

Java

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

yes

Ingres Replicator

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

yes

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

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

User concepts

Access control

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

Administrators, Users, Groups

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Cloudera's HBase PaaS offering now supports Complex Transactions
11 August 2021, Krishna Maheshwari (sponsor)

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