DBMS > BoltDB vs. Heroic vs. Lovefield vs. OrigoDB vs. RocksDB

System Properties Comparison BoltDB vs. Heroic vs. Lovefield vs. OrigoDB vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

An embedded key-value store for Go.

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

Embeddable relational database for web apps written in pure JavaScript

A fully ACID in-memory object graph database

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Key-value store

Time Series DBMS

Relational DBMS

Document store
Object oriented DBMS

Key-value store

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

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

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

github.com/boltdb/bolt

github.com/spotify/heroic

google.github.io/lovefield

origodb.com

rocksdb.org

Technical documentation

spotify.github.io/heroic

github.com/google/lovefield/blob/master/docs/spec_index.md

origodb.com/docs

github.com/facebook/rocksdb/wiki

Developer

Spotify

Google

Robert Friberg et al

Facebook, Inc.

Initial release

2013

2014

2009

under the name LiveDB

2013

Current release

2.1.12, February 2017

8.11.4, April 2024

License

Commercial or Open Source

Open Source

MIT License

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

JavaScript

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
Windows

Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

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

.NET Client API
HTTP API
LINQ

C++ API
Java API

Supported programming languages

JavaScript

.Net

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

Using read-only observers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

horizontal partitioning

client side managed; servers are not synchronized

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

none

Source-replica replication

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

Foreign keys

Referential integrity

yes

depending on model

Transaction concepts

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

yes

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

Write ahead log

yes

In-memory capabilities

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

yes

using MemoryDB

yes

User concepts

Access control

Role based authorization

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