DBMS > BaseX vs. DolphinDB vs. Faircom DB vs. GridGain

System Properties Comparison BaseX vs. DolphinDB vs. Faircom DB vs. GridGain

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Editorial information provided by DB-Engines

Name

Description

Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.

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.

GridGain is an in-memory computing platform, built on Apache Ignite

Primary database model

Native XML DBMS

Time Series DBMS
Vector DBMS

Key-value store
Relational DBMS

Columnar
Key-value store
Object oriented DBMS
Relational DBMS

Secondary database models

Relational DBMS

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

Score	1.56
Rank	#141	Overall
	#4	Native XML DBMS

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

Score	0.18
Rank	#314	Overall
	#45	Key-value stores
	#141	Relational DBMS

Score	1.48
Rank	#150	Overall
	#1	Columnar
	#26	Key-value stores
	#2	Object oriented DBMS
	#69	Relational DBMS

Website

basex.org

www.dolphindb.com

www.faircom.com/products/faircom-db

www.gridgain.com

Technical documentation

docs.basex.org

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

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

www.gridgain.com/docs/index.html

Developer

BaseX GmbH

DolphinDB, Inc

FairCom Corporation

GridGain Systems, Inc.

Initial release

2007

2018

1979

2007

Current release

11.2, August 2024

v2.00.4, January 2022

V13, July 2024

GridGain 8.5.1

License

Commercial or Open Source

Open Source

BSD license

commercial

free community version available

commercial

Restricted, free version available

commercial, open source

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

ANSI C, C++

Java, C++, .Net, Python, REST, SQL

Server operating systems

Linux
OS X
Windows

Linux
Windows

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

easily portable to other OSs

Linux
OS X
Solaris
Windows
z/OS

Data scheme

schema-free

yes

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

yes

Typing

predefined data types such as float or date

XQuery supports types

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes, ANSI SQL with proprietary extensions

ANSI-99 for query and DML statements, subset of DDL

APIs and other access methods

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

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

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

Supported programming languages

Actionscript
C
C#
Haskell
Java
JavaScript

Node.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic

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

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

C#
C++
Java
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes (compute grid and cache interceptors can be used instead)

Triggers

yes

via events

yes

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

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).

yes (replicated cache)

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

multiple readers, single writer

yes

tunable from ACID to Eventually Consistent

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

Users with fine-grained authorization concept on 4 levels

Administrators, Users, Groups

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

Role-based access control
Security Hooks for custom implementations

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