DBMS > Blueflood vs. Ingres vs. SAP SQL Anywhere vs. SWC-DB vs. Transwarp Hippo

System Properties Comparison Blueflood vs. Ingres vs. SAP SQL Anywhere vs. SWC-DB vs. Transwarp Hippo

Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

Well established RDBMS

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

A high performance, scalable Wide Column DBMS

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Primary database model

Secondary database models

Time Series DBMS

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

Score	0.06
Rank	#350	Overall
	#33	Time Series DBMS

Score	3.33
Rank	#78	Overall
	#42	Relational DBMS

Score	2.87
Rank	#88	Overall
	#48	Relational DBMS

Score	0.01
Rank	#373	Overall
	#13	Wide column stores

Score	0.00
Rank	#381	Overall
	#19	Vector DBMS

Website

blueflood.io

www.actian.com/databases/ingres

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

github.com/kashirin-alex/swc-db
www.swcdb.org

www.transwarp.cn/en/subproduct/hippo

Technical documentation

github.com/rax-maas/blueflood/wiki

docs.actian.com/ingres

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Rackspace

Actian Corporation

SAP

formerly Sybase

Alex Kashirin

Initial release

2013

1974

originally developed at University Berkely in early 1970s

1992

2020

2023

Current release

12.0, July 2024

17, July 2015

0.5, April 2021

1.0, May 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

GPL V3

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

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

Linux

Linux
macOS

Data scheme

predefined scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

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.

but tools for importing/exporting data from/to XML-files available

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

HTTP REST

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

ADO.NET
HTTP API
JDBC
ODBC

Proprietary protocol
Thrift

RESTful HTTP API

Supported programming languages

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

C++

C++
Java
Python

Server-side scripts

Stored procedures

yes

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

horizontal partitioning

Ingres Star to access multiple databases simultaneously

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Ingres Replicator

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

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

fine grained access rights according to SQL-standard

Role based access control and fine grained access rights

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