DBMS > Derby vs. DolphinDB vs. Google BigQuery vs. Kyligence Enterprise vs. MarkLogic

System Properties Comparison Derby vs. DolphinDB vs. Google BigQuery vs. Kyligence Enterprise vs. MarkLogic

Editorial information provided by DB-Engines

Name

Description

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

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.

Large scale data warehouse service with append-only tables

A distributed analytics engine for big data, built on top of Apache Kylin

Operational and transactional Enterprise NoSQL database

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Secondary database models

Relational DBMS

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

Score	4.60
Rank	#70	Overall
	#38	Relational DBMS

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.46
Rank	#266	Overall
	#124	Relational DBMS

Score	5.18
Rank	#63	Overall
	#11	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#7	Search engines

Website

db.apache.org/derby

www.dolphindb.com

cloud.google.com/bigquery

kyligence.io/kyligence-enterprise

www.marklogic.com

Technical documentation

db.apache.org/derby/manuals/index.html

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

cloud.google.com/bigquery/docs

docs.marklogic.com

Developer

Apache Software Foundation

DolphinDB, Inc

Google

Kyligence, Inc.

MarkLogic Corp.

Initial release

1997

2018

2010

2016

2001

Current release

10.17.1.0, November 2023

v2.00.4, January 2022

11.0, December 2022

License

Commercial or Open Source

Open Source

Apache version 2

commercial

free community version available

commercial

restricted free version is available

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

Java

C++

Java

C++

Server operating systems

All OS with a Java VM

Linux
Windows

hosted

Linux

Linux
OS X
Windows

Data scheme

yes

schema-free

Schema can be enforced

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

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

yes

ANSI SQL for queries (using Apache Calcite)

yes

SQL92

APIs and other access methods

JDBC

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

RESTful HTTP/JSON API

JDBC
ODBC
RESTful HTTP API

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

Supported programming languages

Java

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

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

Java Stored Procedures

yes

user defined functions

in JavaScript

yes

via XQuery or JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Since BigQuery is designed for querying data

ACID

can act as a resource manager in an XA/JTA transaction

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

yes, with Range Indexes

User concepts

Access control

fine grained access rights according to SQL-standard

Administrators, Users, Groups

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Role-based access control at the document and subdocument levels

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