DBMS > BoltDB vs. Heroic vs. MonetDB vs. WakandaDB vs. Yaacomo

System Properties Comparison BoltDB vs. Heroic vs. MonetDB vs. WakandaDB vs. Yaacomo

Editorial information provided by DB-Engines

Name

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

Description

An embedded key-value store for Go.

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

A relational database management system that stores data in columns

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

Document store
Spatial DBMS

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

Score	0.80
Rank	#215	Overall
	#31	Key-value stores

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	1.72
Rank	#141	Overall
	#64	Relational DBMS

Score	0.10
Rank	#356	Overall
	#16	Object oriented DBMS

Website

github.com/boltdb/bolt

github.com/spotify/heroic

www.monetdb.org

wakanda.github.io

yaacomo.com

Technical documentation

spotify.github.io/heroic

www.monetdb.org/Documentation

wakanda.github.io/doc

Developer

Spotify

MonetDB BV

Wakanda SAS

Q2WEB GmbH

Initial release

2013

2014

2004

2012

2009

Current release

Dec2023 (11.49), December 2023

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

MIT License

Open Source

Apache 2.0

Open Source

Mozilla Public License 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

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

Implementation language

Java

C++, JavaScript

Server operating systems

BSD
Linux
OS X
Solaris
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Android
Linux
Windows

Data 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

yes

via Elasticsearch

yes

SQL

Support of SQL

yes

SQL 2003 with some extensions

yes

APIs and other access methods

HQL (Heroic Query Language, a JSON-based language)
HTTP API

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

RESTful HTTP API

JDBC
ODBC

Supported programming languages

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

JavaScript

Server-side scripts

Stored procedures

yes, in SQL, C, R

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Sharding via remote tables

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

none

Source-replica replication available in experimental status

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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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