DBMS > Blueflood vs. H2 vs. Transwarp Hippo

System Properties Comparison Blueflood vs. H2 vs. Transwarp Hippo

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Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

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

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

Primary database model

Time Series DBMS

Relational DBMS

Vector DBMS

Secondary database models

Spatial DBMS

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

Score	0.06
Rank	#352	Overall
	#36	Time Series DBMS

Score	7.57
Rank	#47	Overall
	#30	Relational DBMS

Score	0.00
Rank	#385	Overall
	#16	Vector DBMS

Website

blueflood.io

www.h2database.com

www.transwarp.cn/en/subproduct/hippo

Technical documentation

github.com/rax-maas/blueflood/wiki

www.h2database.com/html/main.html

Developer

Rackspace

Thomas Mueller

Initial release

2013

2005

2023

Current release

2.2.220, July 2023

1.0, May 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

Linux
OS X

All OS with a Java VM

Linux
macOS

Data scheme

predefined scheme

yes

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

HTTP REST

JDBC
ODBC

RESTful HTTP API

Supported programming languages

Java

C++
Java
Python

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

With clustering: 2 database servers on different computers operate on identical copies of a database

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

yes, multi-version concurrency control (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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