DBMS > Amazon Redshift vs. LevelDB vs. OpenTSDB vs. Riak TS vs. YDB

System Properties Comparison Amazon Redshift vs. LevelDB vs. OpenTSDB vs. Riak TS vs. YDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

Scalable Time Series DBMS based on HBase

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

A distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API

Primary database model

Relational DBMS

Key-value store

Time Series DBMS

Document store
Relational DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	1.68
Rank	#142	Overall
	#12	Time Series DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Score	0.33
Rank	#287	Overall
	#43	Document stores
	#132	Relational DBMS

Website

aws.amazon.com/redshift

github.com/google/leveldb

opentsdb.net

github.com/ydb-platform/ydb
ydb.tech

Technical documentation

docs.aws.amazon.com/redshift

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

opentsdb.net/docs/build/html/index.html

www.tiot.jp/riak-docs/riak/ts/latest

ydb.tech/en/docs

Developer

Amazon (based on PostgreSQL)

Google

currently maintained by Yahoo and other contributors

Open Source, formerly Basho Technologies

Yandex

Initial release

2012

2011

2015

2019

Current release

1.23, February 2021

3.0.0, September 2022

License

Commercial or Open Source

commercial

Open Source

BSD

Open Source

LGPL

Open Source

Apache 2.0; commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Java

Erlang

Server operating systems

hosted

Illumos
Linux
OS X
Windows

Linux
Windows

Linux
OS X

Linux

Data scheme

yes

schema-free

Flexible Schema (defined schema, partial schema, schema free)

Typing

predefined data types such as float or date

yes

numeric data for metrics, strings for tags

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

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes, limited

SQL-like query language (YQL)

APIs and other access methods

JDBC
ODBC

HTTP API
Telnet API

HTTP API
Native Erlang Interface

RESTful HTTP API (DynamoDB compatible)

Supported programming languages

All languages supporting JDBC/ODBC

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

Erlang
Go
Java
Python
R
Ruby

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Go
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in Python

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

based on HBase

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

selectable replication factor

based on HBase

selectable replication factor

Active-passive shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

based on HBase

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

links between datasets can be stored

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

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

Access rights defined for Yandex Cloud users

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