DBMS > LevelDB vs. TimescaleDB vs. WakandaDB vs. Yaacomo

System Properties Comparison LevelDB vs. TimescaleDB vs. WakandaDB vs. Yaacomo

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Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

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

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Secondary database models

Relational DBMS

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

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

github.com/google/leveldb

www.timescale.com

wakanda.github.io

yaacomo.com

Technical documentation

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

docs.timescale.com

wakanda.github.io/doc

Developer

Google

Timescale

Wakanda SAS

Q2WEB GmbH

Initial release

2011

2017

2012

2009

Current release

1.23, February 2021

2.13.0, November 2023

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

BSD

Open Source

Apache 2.0

Open Source

AGPLv3, extended commercial license available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C++, JavaScript

Server operating systems

Illumos
Linux
OS X
Windows

Linux
OS X
Windows

Android
Linux
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

Secondary indexes

yes

SQL

Support of SQL

yes

full PostgreSQL SQL syntax

yes

APIs and other access methods

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

RESTful HTTP API

JDBC
ODBC

Supported programming languages

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

JavaScript

Server-side scripts

Stored procedures

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes, across time and space (hash partitioning) attributes

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication with hot standby and reads on replicas

none

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

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

yes

fine grained access rights according to SQL-standard

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