DBMS > BigObject vs. Dolt vs. RethinkDB vs. RocksDB vs. XTDB

System Properties Comparison BigObject vs. Dolt vs. RethinkDB vs. RocksDB vs. XTDB

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

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

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

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

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Secondary database models

Document store

Spatial DBMS

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

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	1.02
Rank	#191	Overall
	#89	Relational DBMS

Score	2.66
Rank	#107	Overall
	#20	Document stores

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

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

bigobject.io

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

rethinkdb.com

rocksdb.org

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

docs.bigobject.io

docs.dolthub.com

rethinkdb.com/docs

github.com/facebook/rocksdb/wiki

www.xtdb.com/docs

Developer

BigObject, Inc.

DoltHub Inc

The Linux Foundation

since July 2017

Facebook, Inc.

Juxt Ltd.

Initial release

2015

2018

2009

2013

2019

Current release

2.4.1, August 2020

9.2.1, May 2024

1.19, September 2021

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache Version 2.0

Open Source

Apache Version 2

Open Source

BSD

Open Source

MIT License

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

C++

Clojure

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
macOS
Windows

Linux
OS X
Windows

Linux

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

yes, extensible-data-notation format

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

SQL

Support of SQL

SQL-like DML and DDL statements

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

CLI Client
HTTP REST

C++ API
Java API

HTTP REST
JDBC

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

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

C
C++
Go
Java
Perl
Python
Ruby

Clojure
Java

Server-side scripts

Stored procedures

Lua

yes

currently in alpha release

Triggers

yes

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

range based

horizontal partitioning

none

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.

Source-replica replication

yes

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

Atomic single-document operations

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

MVCC based

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

yes

users and table-level permissions

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