DBMS > DolphinDB vs. Google Cloud Bigtable vs. MonetDB vs. SQream DB

System Properties Comparison DolphinDB vs. Google Cloud Bigtable vs. MonetDB vs. SQream DB

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Editorial information provided by DB-Engines

Name

Description

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.

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

A relational database management system that stores data in columns

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Time Series DBMS
Vector DBMS

Key-value store
Wide column store

Relational DBMS

Secondary database models

Relational DBMS

Document store
Spatial DBMS

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

Score	2.72
Rank	#100	Overall
	#8	Time Series DBMS
	#5	Vector DBMS

Score	2.97
Rank	#92	Overall
	#15	Key-value stores
	#8	Wide column stores

Score	1.72
Rank	#135	Overall
	#62	Relational DBMS

Score	0.62
Rank	#234	Overall
	#109	Relational DBMS

Website

www.dolphindb.com

cloud.google.com/bigtable

www.monetdb.org

sqream.com

Technical documentation

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

cloud.google.com/bigtable/docs

www.monetdb.org/Documentation

docs.sqream.com

Developer

DolphinDB, Inc

Google

MonetDB BV

SQream Technologies

Initial release

2018

2015

2004

2017

Current release

v2.00.4, January 2022

Dec2023 (11.49), December 2023

2022.1.6, December 2022

License

Commercial or Open Source

commercial

free community version available

commercial

Open Source

Mozilla Public License 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

C++

C++, CUDA, Haskell, Java, Scala

Server operating systems

Linux
Windows

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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

SQL-like query language

yes

SQL 2003 with some extensions

yes

APIs and other access methods

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

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

.Net
JDBC
ODBC

Supported programming languages

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

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

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

yes, in SQL, C, R

user defined functions in Python

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Sharding via remote tables

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Internal replication in Colossus, and regional replication between two clusters in different zones

none

Source-replica replication available in experimental status

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

Atomic single-row operations

ACID

Concurrency

Support for concurrent manipulation of data

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

Administrators, Users, Groups

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

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