DBMS > Drizzle vs. InfinityDB vs. RavenDB vs. Transwarp Hippo

System Properties Comparison Drizzle vs. InfinityDB vs. RavenDB vs. Transwarp Hippo

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

A Java embedded Key-Value Store which extends the Java Map interface

Open Source Operational and Transactional Enterprise NoSQL Document Database

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

Primary database model

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.00
Rank	#378	Overall
	#57	Key-value stores

Score	2.92
Rank	#101	Overall
	#18	Document stores

Score	0.00
Rank	#383	Overall
	#13	Vector DBMS

Website

boilerbay.com

ravendb.net

www.transwarp.cn/en/subproduct/hippo

Technical documentation

boilerbay.com/infinitydb/manual

ravendb.net/docs

Developer

Drizzle project, originally started by Brian Aker

Boiler Bay Inc.

Hibernating Rhinos

Initial release

2008

2002

2010

2023

Current release

7.2.4, September 2012

4.0

5.4, July 2022

1.0, May 2023

License

Commercial or Open Source

Open Source

GNU GPL

commercial

Open Source

AGPL version 3, commercial license available

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

C++

Java

C++

Server operating systems

FreeBSD
Linux
OS X

All OS with a Java VM

Linux
macOS
Raspberry Pi
Windows

Linux
macOS

Data scheme

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

schema-free

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

manual creation possible, using inversions based on multi-value capability

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-like query language (RQL)

APIs and other access methods

JDBC

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

RESTful HTTP API

Supported programming languages

C
C++
Java
PHP

Java

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C++
Java
Python

Server-side scripts

Stored procedures

yes

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

READ-COMMITTED or SERIALIZED

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Immediate Consistency

Foreign keys

Referential integrity

yes

manual creation possible, using inversions based on multi-value capability

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

ACID, Cluster-wide transaction available

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

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Authorization levels configured per client per database

Role based access control and fine grained access rights

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More resources

DB-Engines blog posts

MySQL won the April ranking; did its forks follow?
1 April 2015, Paul Andlinger

Has MySQL finally lost its mojo?
1 July 2013, Matthias Gelbmann

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