DBMS > DolphinDB vs. FileMaker vs. Google Cloud Bigtable vs. PostGIS

System Properties Comparison DolphinDB vs. FileMaker vs. Google Cloud Bigtable vs. PostGIS

Please select another system to include it in the comparison.

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.

FileMaker is a cross-platform RDBMS that includes a GUI frontend.

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

Spatial extension of PostgreSQL

Primary database model

Time Series DBMS

Relational DBMS

Key-value store
Wide column store

Spatial 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	48.20
Rank	#20	Overall
	#14	Relational DBMS

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	22.69
Rank	#29	Overall
	#1	Spatial DBMS

Website

www.dolphindb.com

www.claris.com/filemaker

cloud.google.com/bigtable

postgis.net

Technical documentation

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

www.claris.com/resources/documentation

cloud.google.com/bigtable/docs

postgis.net/documentation

Developer

DolphinDB, Inc

Claris

a subsidiary of Apple

Google

Initial release

2018

1983

2015

2005

Current release

v2.00.4, January 2022

19.4.1, November 2021

3.4.2, February 2024

License

Commercial or Open Source

commercial

free community version available

commercial

Open Source

GPL v2.0

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++

Server operating systems

Linux
Windows

iOS

client part only
Linux
OS X
Windows

hosted

Data scheme

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.

yes

A http query request can return the data in XML format

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

via plugins

yes

APIs and other access methods

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

Filemaker WebDirect
JDBC
ODBC

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

Supported programming languages

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

PHP

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

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Sharding

yes

based on PostgreSQL

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication, warm standby

since Version 14

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

yes

based on PostgreSQL

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

simple rights management via user accounts and connection to external directory services

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

yes

based on PostgreSQL

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

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

show all

Recent citations in the news

Tilda Swinton on 'Problemista' Fan Horror Stories About Her Character
1 March 2024, IndieWire

Reviews - Features
1 March 2024, Reverse Shot

Apple Filed for new Trademarks in the U.S. and Hong Kong this week for the Figurative Version of 'Reality Composer ...
15 October 2023, Patently Apple

Apple Subsidiary to Face Worker's Job Loss Claims, but Not Apple
14 February 2024, Bloomberg Law

Apple subsidiary FileMaker returns to its original name from the '80s
6 August 2019, The Verge

provided by Google News

Google expands BigQuery with Gemini, brings vector support to cloud databases
29 February 2024, VentureBeat

Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs
31 January 2022, InfoQ.com

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

Google scales up Cloud Bigtable NoSQL database
27 January 2022, TechTarget

Google Cloud makes it cheaper to run smaller workloads on Bigtable
7 April 2020, TechCrunch

provided by Google News

Share this page