DBMS > LevelDB vs. Pinecone vs. Postgres-XL vs. Tkrzw

System Properties Comparison LevelDB vs. Pinecone vs. Postgres-XL vs. Tkrzw

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Editorial information provided by DB-Engines

Name

Description

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

A managed, cloud-native vector database

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

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

Primary database model

Secondary database models

Document store
Spatial DBMS

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

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

Score	3.23
Rank	#92	Overall
	#3	Vector DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

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

Website

github.com/google/leveldb

www.pinecone.io

www.postgres-xl.org

dbmx.net/tkrzw

Technical documentation

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

docs.pinecone.io/docs/overview

www.postgres-xl.org/documentation

Developer

Google

Pinecone Systems, Inc

Mikio Hirabayashi

Initial release

2011

2019

2014

since 2012, originally named StormDB

2020

Current release

1.23, February 2021

10 R1, October 2018

0.9.3, August 2020

License

Commercial or Open Source

Open Source

BSD

commercial

Open Source

Mozilla public license

Open Source

Apache Version 2.0

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++

Server operating systems

Illumos
Linux
OS X
Windows

hosted

Linux
macOS

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

String, Number, Boolean

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.

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

distributed, parallel query execution

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

Python

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

Transaction concepts

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

ACID

MVCC

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

using specific database classes

User concepts

Access control

fine grained access rights according to SQL-standard

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