DBMS > BigObject vs. BoltDB vs. Heroic vs. LevelDB vs. OpenQM

System Properties Comparison BigObject vs. BoltDB vs. Heroic vs. LevelDB vs. OpenQM

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

An embedded key-value store for Go.

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

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

QpenQM is a high-performance, self-tuning, multi-value DBMS

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	0.74
Rank	#220	Overall
	#31	Key-value stores

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

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

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Website

bigobject.io

github.com/boltdb/bolt

github.com/spotify/heroic

github.com/google/leveldb

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

Technical documentation

docs.bigobject.io

spotify.github.io/heroic

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

Developer

BigObject, Inc.

Spotify

Google

Rocket Software, originally Martin Phillips

Initial release

2015

2013

2014

2011

1993

Current release

1.23, February 2021

3.4-12

License

Commercial or Open Source

commercial

free community edition available

Open Source

MIT License

Open Source

Apache 2.0

Open Source

BSD

Open Source

GPLv2, extended commercial license 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++

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

BSD
Linux
OS X
Solaris
Windows

Illumos
Linux
OS X
Windows

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Data scheme

yes

schema-free

yes

with some exceptions

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.

yes

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

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

Supported programming languages

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

.Net
Basic
C
Java
Objective C
PHP
Python

Server-side scripts

Stored procedures

Lua

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

none

yes

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

automatically between fact table and dimension tables

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

Access rights can be defined down to the item level

More information provided by the system vendor

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