DBMS > Apache Phoenix vs. Google BigQuery vs. Raima Database Manager vs. TDSQL for MySQL

System Properties Comparison Apache Phoenix vs. Google BigQuery vs. Raima Database Manager vs. TDSQL for MySQL

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

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

Large scale data warehouse service with append-only tables

RDBMS with a small footprint, either embedded into an application or used as a database server

A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.

Primary database model

Relational DBMS

Relational DBMS
Time Series DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.46
Rank	#259	Overall
	#120	Relational DBMS
	#22	Time Series DBMS

Score	0.85
Rank	#205	Overall
	#95	Relational DBMS

Website

phoenix.apache.org

cloud.google.com/bigquery

raima.com

www.tencentcloud.com/products/dcdb

Technical documentation

phoenix.apache.org

cloud.google.com/bigquery/docs

docs.raima.com

www.tencentcloud.com/document/product/1042

Developer

Apache Software Foundation

Google

Raima Inc.

Tencent

Initial release

2014

2010

1984

2013

Current release

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

15, June 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

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

Server operating systems

Linux
Unix
Windows

hosted

Android
HP-UX
Integrity RTOS
iOS
Linux
OS X
QNX
Solaris
VxWorks
Windows

hosted

Data scheme

yes

late-bound, schema-on-read capabilities

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.

Exporting/Importing of XML structures possible

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

JDBC

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
RESTful HTTP API

JDBC
ODBC

Supported programming languages

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

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C
C++
Objective-C
PL/SQL

C
C#
C++
Java
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

based on the ANSI/ISO SQL Persistent Stored Modules (PSM) specification

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

Multi-source replication
Source-replica replication

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

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (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

User concepts

Access control

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

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Users with fine-grained authorization concept

More information provided by the system vendor

Specific characteristics

Raima Database Manager (RDM) is an embedded time-series database optimized to run...
» more

Competitive advantages

Decreased time-to-market Industry-standard interfaces & tools for making your job...
» more

Typical application scenarios

Typical use cases include: Internet of Things (IoT) Embedded In-Memory Database Time-Series...
» more

Key customers

Infor, ABB, The Boeing Company, BAE Systems, Dow Jones, Dun & Bradstreet, Fujitsu,...
» more

Market metrics

Over 30 000 applications developers worldwide have field-tested RDM products More...
» more

Licensing and pricing models

Just as the technical aspects of Raima Database Manager are flexible, so are the...
» more

News

Raima Unveils RaimaDB 16.0: Elevating Database Performance and User Experience
29 February 2024

Raima Announces Release of Raima Database Manager (RDM) v15, a Powerful Embedded Time Series Database
10 June 2021

Raima Announces Release of Raima Database Manager (RDM) v14.2, a Powerful IoT Edge Embedded Database
8 October 2020

Raima Joins BlackBerry QNX Channel Partner Program to Deliver Safety-Critical and Secure Software Solutions
1 October 2020

Raima Expands Their Reseller Network in Asia
19 May 2020

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.