DBMS > Blueflood vs. LevelDB vs. Riak KV vs. TimesTen vs. Vitess

System Properties Comparison Blueflood vs. LevelDB vs. Riak KV vs. TimesTen vs. Vitess

Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

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

Distributed, fault tolerant key-value store

In-Memory RDBMS compatible to Oracle

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Time Series DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.13
Rank	#346	Overall
	#33	Time Series DBMS

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

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Score	0.88
Rank	#203	Overall
	#95	Relational DBMS

Website

blueflood.io

github.com/google/leveldb

www.oracle.com/database/technologies/related/timesten.html

vitess.io

Technical documentation

github.com/rax-maas/blueflood/wiki

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

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

docs.oracle.com/database/timesten-18.1

vitess.io/docs

Developer

Rackspace

Google

OpenSource, formerly Basho Technologies

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

The Linux Foundation, PlanetScale

Initial release

2013

2011

2009

1998

2013

Current release

1.23, February 2021

3.2.0, December 2022

11 Release 2 (11.2.2.8.0)

15.0.2, December 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

BSD

Open Source

Apache version 2, commercial enterprise edition

commercial

Open Source

Apache Version 2.0, commercial licenses available

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

Java

C++

Erlang

Server operating systems

Linux
OS X

Illumos
Linux
OS X
Windows

Linux
OS X

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Docker
Linux
macOS

Data scheme

predefined scheme

schema-free

yes

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

restricted

yes

SQL

Support of SQL

yes

with proprietary extensions

APIs and other access methods

HTTP REST

HTTP API
Native Erlang Interface

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

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

C
C++
Java
PL/SQL

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

Erlang

PL/SQL

yes

proprietary syntax

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

Sharding

no "single point of failure"

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

none

selectable replication factor

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

links between data sets can be stored

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

with automatic compression on writes

yes

by means of logfiles and checkpoints

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

yes, using Riak Security

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

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