DBMS > DolphinDB vs. FatDB vs. Manticore Search vs. Spark SQL

System Properties Comparison DolphinDB vs. FatDB vs. Manticore Search vs. Spark SQL

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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.

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.

Multi-storage database for search, including full-text search.

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Time Series DBMS

Document store
Key-value store

Search engine

Relational DBMS

Secondary database models

Relational DBMS

Time Series DBMS

using the Manticore Columnar Library

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

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

www.dolphindb.com

manticoresearch.com

spark.apache.org/sql

Technical documentation

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

manual.manticoresearch.com

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

DolphinDB, Inc

FatCloud

Manticore Software

Apache Software Foundation

Initial release

2018

2012

2017

2014

Current release

v2.00.4, January 2022

6.0, February 2023

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

free community version available

commercial

Open Source

GPL version 2

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Scala

Server operating systems

Linux
Windows

Windows

FreeBSD
Linux
macOS
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

Fixed schema

yes

Typing

predefined data types such as float or date

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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.

Can index from XML

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

SQL-like query language

Via inetgration in SQL Server

SQL-like query language

SQL-like DML and DDL statements

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

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

JDBC
ODBC

Supported programming languages

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

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

Java
Python
R
Scala

Server-side scripts

Stored procedures

yes

via applications

user defined functions

Triggers

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Partitioning is done manually, search queries against distributed index is supported

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Synchronous replication based on Galera library

none

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

Foreign keys

Referential integrity

Transaction concepts

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

yes

isolated transactions for atomic changes and binary logging for safe writes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Manticore index.

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

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