DBMS > Hypertable vs. LevelDB vs. OpenMLDB vs. Sequoiadb

System Properties Comparison Hypertable vs. LevelDB vs. OpenMLDB vs. Sequoiadb

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Editorial information provided by DB-Engines

Name

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

Description

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

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

An open-source machine learning database that provides a feature platform for training and inference

NewSQL database with distributed OLTP and SQL

Primary database model

Wide column store

Key-value store

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	2.33
Rank	#111	Overall
	#19	Key-value stores

Score	0.11
Rank	#339	Overall
	#30	Time Series DBMS

Score	0.42
Rank	#263	Overall
	#41	Document stores
	#121	Relational DBMS

Website

github.com/google/leveldb

openmldb.ai

www.sequoiadb.com

Technical documentation

github.com/google/leveldb/blob/main/doc/index.md

openmldb.ai/docs/zh/main

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Hypertable Inc.

Google

4 Paradigm Inc.

Sequoiadb Ltd.

Initial release

2009

2011

2020

2013

Current release

0.9.8.11, March 2016

1.23, February 2021

2024-2 February 2024

License

Commercial or Open Source

Open Source

GNU version 3. Commercial license available

Open Source

BSD

Open Source

Server: AGPL; Client: Apache V2

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++, Java, Scala

C++

Server operating systems

Linux
OS X
Windows

an inofficial Windows port is available

Illumos
Linux
OS X
Windows

Linux

Data scheme

schema-free

Fixed schema

schema-free

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

C++ API
Thrift

JDBC
SQLAlchemy

proprietary protocol using JSON

Supported programming languages

C++
Java
Perl
PHP
Python
Ruby

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C++
Go
Java
Python
Scala

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

JavaScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor on file system level

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

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

simple password-based access control

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