DBMS > DolphinDB vs. Faircom DB vs. FatDB vs. Google Cloud Spanner vs. Yaacomo

System Properties Comparison DolphinDB vs. Faircom DB vs. FatDB vs. Google Cloud Spanner 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.

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

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

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

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

Primary database model

Time Series DBMS

Key-value store
Relational DBMS

Document store
Key-value store

Relational DBMS

Secondary database models

Relational DBMS

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

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	0.20
Rank	#318	Overall
	#48	Key-value stores
	#141	Relational DBMS

Score	2.89
Rank	#103	Overall
	#52	Relational DBMS

Website

www.dolphindb.com

www.faircom.com/products/faircom-db

cloud.google.com/spanner

yaacomo.com

Technical documentation

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

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

cloud.google.com/spanner/docs

Developer

DolphinDB, Inc

FairCom Corporation

FatCloud

Google

Q2WEB GmbH

Initial release

2018

1979

2012

2017

2009

Current release

v2.00.4, January 2022

V12, November 2020

License

Commercial or Open Source

commercial

free community version available

commercial

Restricted, free version available

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++

ANSI C, C++

Server operating systems

Linux
Windows

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

Windows

hosted

Android
Linux
Windows

Data scheme

yes

schema free, schema optional, schema required, partial schema,

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, ANSI SQL Types, JSON, typed binary structures

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

yes, ANSI SQL with proprietary extensions

Via inetgration in SQL Server

yes

Query statements complying to ANSI 2011

yes

APIs and other access methods

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

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

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

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

JDBC
ODBC

Supported programming languages

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

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

via applications

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

selectable replication factor

Multi-source replication with 3 replicas for regional instances.

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

Transaction concepts

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

yes

tunable from ACID to Eventually Consistent

ACID

Strict serializable isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Yes, tunable from durable to delayed durability to in-memory

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

Fine grained access rights according to SQL-standard with additional protections for files

Can implement custom security layer via applications

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

fine grained access rights according to SQL-standard

More information provided by the system vendor

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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

FairCom kicks off new era of database technology USA - English
10 November 2020, PR Newswire

provided by Google News

Google Improves Cloud Spanner: More Compute and Storage without Price Increase
14 October 2023, InfoQ.com

Google turns up the heat on AWS, claims Cloud Spanner is half the cost of DynamoDB
11 October 2023, TechCrunch

Google makes its Cloud Spanner database service faster and more cost-efficient
11 October 2023, SiliconANGLE News

Google Cloud Spanner competes directly with Amazon DynamoDB
12 October 2023, Techzine Europe

More AI Added to Google Cloud's Databases
28 February 2024, Datanami

provided by Google News

Share this page