DBMS > Dolt vs. Google BigQuery vs. KeyDB vs. ObjectBox

System Properties Comparison Dolt vs. Google BigQuery vs. KeyDB vs. ObjectBox

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Editorial information provided by DB-Engines

Name

Description

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

Large scale data warehouse service with append-only tables

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

Extremely fast embedded database for small devices, IoT and Mobile

Primary database model

Relational DBMS

Key-value store

Object oriented DBMS

Secondary database models

Document store

Time Series DBMS

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

Score	1.02
Rank	#191	Overall
	#89	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.70
Rank	#229	Overall
	#32	Key-value stores

Score	1.29
Rank	#166	Overall
	#5	Object oriented DBMS

Website

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

cloud.google.com/bigquery

github.com/Snapchat/KeyDB
keydb.dev

objectbox.io

Technical documentation

docs.dolthub.com

cloud.google.com/bigquery/docs

docs.keydb.dev

docs.objectbox.io

Developer

DoltHub Inc

Google

EQ Alpha Technology Ltd.

ObjectBox Limited

Initial release

2018

2010

2019

2017

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

BSD-3

Open Source

Apache License 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

C and C++

Server operating systems

Linux
macOS
Windows

hosted

Linux

Android
iOS
Linux
macOS
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

by using the Redis Search module

yes

SQL

Support of SQL

yes

APIs and other access methods

CLI Client
HTTP REST

RESTful HTTP/JSON API

Proprietary protocol

RESP - REdis Serialization Protoco

Proprietary native 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
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

Server-side scripts

Stored procedures

yes

currently in alpha release

user defined functions

in JavaScript

Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

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
Source-replica replication

online/offline synchronization between client and server

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

Optimistic locking, atomic execution of commands blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

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

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

simple password-based access control and ACL

yes

More information provided by the system vendor

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