DBMS > DolphinDB vs. FatDB vs. PlanetScale vs. Warp 10 vs. Yaacomo

System Properties Comparison DolphinDB vs. FatDB vs. PlanetScale vs. Warp 10 vs. Yaacomo

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

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.

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Scalable, distributed, serverless MySQL database platform built on top of Vitess

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Time Series DBMS

Document store
Key-value store

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Relational DBMS

Document store
Spatial DBMS

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

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	1.49
Rank	#155	Overall
	#72	Relational DBMS

Score	0.14
Rank	#344	Overall
	#32	Time Series DBMS

Website

www.dolphindb.com

planetscale.com

www.warp10.io

yaacomo.com

Technical documentation

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

planetscale.com/docs

www.warp10.io/content/02_Getting_started

Developer

DolphinDB, Inc

FatCloud

PlanetScale

SenX

Q2WEB GmbH

Initial release

2018

2012

2020

2015

2009

Current release

v2.00.4, January 2022

License

Commercial or Open Source

commercial

free community version available

commercial

Open Source

Apache 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++

Java

Server operating systems

Linux
Windows

Windows

Docker
Linux
macOS

Linux
OS X
Windows

Android
Linux
Windows

Data scheme

yes

schema-free

yes

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

Via inetgration in SQL Server

yes

with proprietary extensions

yes

APIs and other access methods

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

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

ADO.NET
JDBC
MySQL protocol
ODBC

HTTP API
Jupyter
WebSocket

JDBC
ODBC

Supported programming languages

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

via applications

yes

proprietary syntax

yes

WarpScript

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

based on HBase

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Multi-source replication
Source-replica replication

selectable replication factor

based on HBase

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Immediate Consistency

based on HBase

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

yes

ACID at shard level

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

Can implement custom security layer via applications

Users with fine-grained authorization concept

no user groups or roles

Mandatory use of cryptographic tokens, containing fine-grained authorizations

fine grained access rights according to SQL-standard

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