DBMS > Drizzle vs. Hypertable vs. LMDB vs. ReductStore

System Properties Comparison Drizzle vs. Hypertable vs. LMDB vs. ReductStore

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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.

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

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

An open source BigTable implementation based on distributed file systems such as Hadoop

A high performant, light-weight, embedded key-value database library

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

Primary database model

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

Score	1.99
Rank	#125	Overall
	#21	Key-value stores

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

www.symas.com/symas-embedded-database-lmdb

github.com/reductstore
www.reduct.store

Technical documentation

www.lmdb.tech/doc

www.reduct.store/docs

Developer

Drizzle project, originally started by Brian Aker

Hypertable Inc.

Symas

ReductStore LLC

Initial release

2008

2009

2011

2023

Current release

7.2.4, September 2012

0.9.8.11, March 2016

0.9.32, January 2024

1.9, March 2024

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

GNU version 3. Commercial license available

Open Source

Business Source License 1.1

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++

C++, Rust

Server operating systems

FreeBSD
Linux
OS X

Linux
OS X
Windows

an inofficial Windows port is available

Linux
Unix
Windows

Docker
Linux
macOS
Windows

Data scheme

yes

schema-free

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

restricted

only exact value or prefix value scans

SQL

Support of SQL

yes

with proprietary extensions

APIs and other access methods

JDBC

C++ API
Thrift

HTTP API

Supported programming languages

C
C++
Java
PHP

C++
Java
Perl
PHP
Python
Ruby

.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl

C++
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

Triggers

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

selectable replication factor on file system level

none

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

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

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

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