DBMS > DolphinDB vs. Google BigQuery vs. MonetDB vs. SAP Adaptive Server vs. SAP Advantage Database Server

System Properties Comparison DolphinDB vs. Google BigQuery vs. MonetDB vs. SAP Adaptive Server vs. SAP Advantage Database Server

Editorial information provided by DB-Engines

Name

SAP Advantage Database Server seems to be discontinued. Therefore it is excluded 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.

Large scale data warehouse service with append-only tables

A relational database management system that stores data in columns

The SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMS

Low-cost RDBMS with access to ISAM and FoxPro data structures

Primary database model

Time Series DBMS

Relational DBMS

Secondary database models

Relational DBMS

Document store
Spatial DBMS

Spatial DBMS

with Boeing's Spatial Query Server

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

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	1.72
Rank	#141	Overall
	#64	Relational DBMS

Score	35.09
Rank	#25	Overall
	#17	Relational DBMS

Website

www.dolphindb.com

cloud.google.com/bigquery

www.monetdb.org

www.sap.com/products/technology-platform/sybase-ase.html

www.sap.com/products/advantage-database-server.html

Technical documentation

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

cloud.google.com/bigquery/docs

www.monetdb.org/Documentation

help.sap.com/docs/SAP_ASE

Developer

DolphinDB, Inc

Google

MonetDB BV

SAP, Sybase

Sybase, SAP

Initial release

2018

2010

2004

1987

1993

Current release

v2.00.4, January 2022

Dec2023 (11.49), December 2023

16.0

License

Commercial or Open Source

commercial

free community version available

commercial

Open Source

Mozilla Public License 2.0

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++

C and C++

Server operating systems

Linux
Windows

hosted

FreeBSD
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Unix
Windows

Linux
Windows

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

SQL 2003 with some extensions

yes

APIs and other access methods

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

RESTful HTTP/JSON API

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

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

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

C
C++
Cobol
Java
Java
Perl
PHP
Python

Delphi
Perl
PHP

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

yes, in SQL, C, R

Java and Transact-SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Sharding via remote tables

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Source-replica replication available in experimental status

Multi-source replication
Source-replica replication

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

yes

Since BigQuery is designed for querying data

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

caching of (temporary) tables can be configured

User concepts

Access control

Administrators, Users, Groups

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

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

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