DBMS > Blueflood vs. DolphinDB vs. Realm vs. SAP SQL Anywhere

System Properties Comparison Blueflood vs. DolphinDB vs. Realm vs. SAP SQL Anywhere

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Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

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.

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

Time Series DBMS

Document store

Relational DBMS

Secondary database models

Relational DBMS

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

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Website

blueflood.io

www.dolphindb.com

realm.io

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

github.com/rax-maas/blueflood/wiki

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

realm.io/docs

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Rackspace

DolphinDB, Inc

Realm, acquired by MongoDB in May 2019

SAP

formerly Sybase

Initial release

2013

2018

2014

1992

Current release

v2.00.4, January 2022

17, July 2015

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free community version available

Open Source

commercial

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++

Server operating systems

Linux
OS X

Linux
Windows

Android
Backend: server-less
iOS
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

predefined 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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

HTTP REST

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

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

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

.Net
Java

with Android only
Objective-C
React Native
Swift

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

Server-side scripts

Stored procedures

yes

runs within the applications so server-side scripts are unnecessary

yes, in C/C++, Java, .Net or Perl

Triggers

yes

Change Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes

none

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

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

In-Memory realm

yes

User concepts

Access control

Administrators, Users, Groups

yes

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

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