DBMS > BoltDB vs. Dolt vs. GigaSpaces vs. IRONdb vs. RocksDB

System Properties Comparison BoltDB vs. Dolt vs. GigaSpaces vs. IRONdb vs. RocksDB

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

A MySQL compatible DBMS with Git-like versioning of data and schema

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

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

Primary database model

Key-value store

Relational DBMS

Document store
Object oriented DBMS

Values are user defined objects

Time Series DBMS

Key-value store

Secondary database models

Document store

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Trend Chart

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

Score	1.02
Rank	#191	Overall
	#89	Relational DBMS

Score	1.03
Rank	#188	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

github.com/boltdb/bolt

github.com/dolthub/dolt
www.dolthub.com

www.gigaspaces.com

www.circonus.com/solutions/time-series-database/

rocksdb.org

Technical documentation

docs.dolthub.com

docs.gigaspaces.com/latest/landing.html

docs.circonus.com/irondb/category/getting-started

github.com/facebook/rocksdb/wiki

Developer

DoltHub Inc

Gigaspaces Technologies

Circonus LLC.

Facebook, Inc.

Initial release

2013

2018

2000

2017

2013

Current release

15.5, September 2020

V0.10.20, January 2018

9.2.1, May 2024

License

Commercial or Open Source

Open Source

MIT License

Open Source

Apache Version 2.0

Open Source

Apache Version 2; Commercial licenses available

commercial

Open Source

BSD

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++, .Net

C and C++

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
macOS
Windows

Linux
macOS
Solaris
Windows

Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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.

XML can be used for describing objects metadata

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-99 for query and DML statements

SQL-like query language (Circonus Analytics Query Language: CAQL)

APIs and other access methods

CLI Client
HTTP REST

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

HTTP API

C++ API
Java API

Supported programming languages

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
C++
Java
Python
Scala

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

currently in alpha release

yes

yes, in Lua

Triggers

yes

yes, event driven architecture

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Automatic, metric affinity per node

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

A database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

configurable replication factor, datacenter aware

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate consistency per node, eventual consistency across nodes

Foreign keys

Referential integrity

yes

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

In-memory capabilities

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

yes

User concepts

Access control

Only one user is configurable, and must be specified in the config file at startup

Role-based access control

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