DBMS > FeatureBase vs. LevelDB vs. Tkrzw vs. VoltDB

System Properties Comparison FeatureBase vs. LevelDB vs. Tkrzw vs. VoltDB

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Editorial information provided by DB-Engines

Name

Description

Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.

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

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Relational DBMS

Key-value store

Relational DBMS

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

Score	0.31
Rank	#292	Overall
	#135	Relational DBMS

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

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

www.featurebase.com

github.com/google/leveldb

dbmx.net/tkrzw

www.voltdb.com

Technical documentation

docs.featurebase.com

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

docs.voltdb.com

Developer

Molecula and Pilosa Open Source Contributors

Google

Mikio Hirabayashi

VoltDB Inc.

Initial release

2017

2011

2020

2010

Current release

2022, May 2022

1.23, February 2021

0.9.3, August 2020

11.3, April 2022

License

Commercial or Open Source

commercial

Open Source

BSD

Open Source

Apache Version 2.0

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

Linux
macOS

Illumos
Linux
OS X
Windows

Linux
macOS

Linux
OS X

for development

Data scheme

yes

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

yes

SQL

Support of SQL

SQL queries

yes

only a subset of SQL 99

APIs and other access methods

gRPC
JDBC
Kafka Connector
ODBC

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

Java
Python

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C++
Java
Python
Ruby

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

Java

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

yes

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes, using Linux fsync

yes

with automatic compression on writes

yes

Snapshots and command logging

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using specific database classes

User concepts

Access control

Users and roles with access to stored procedures

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