DBMS > atoti vs. Bangdb vs. Lovefield vs. Vitess

System Properties Comparison atoti vs. Bangdb vs. Lovefield vs. Vitess

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Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

Converged and high performance database for device data, events, time series, document and graph

Embeddable relational database for web apps written in pure JavaScript

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Object oriented DBMS

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

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

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	0.82
Rank	#209	Overall
	#97	Relational DBMS

Website

atoti.io

bangdb.com

google.github.io/lovefield

vitess.io

Technical documentation

docs.atoti.io

docs.bangdb.com

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

vitess.io/docs

Developer

ActiveViam

Sachin Sinha, BangDB

Google

The Linux Foundation, PlanetScale

Initial release

2012

2014

2013

Current release

BangDB 2.0, October 2021

2.1.12, February 2017

15.0.2, December 2022

License

Commercial or Open Source

commercial

free versions available

Open Source

BSD 3

Open Source

Apache 2.0

Open Source

Apache Version 2.0, commercial licenses 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, C++

JavaScript

Server operating systems

Linux

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

tested with Chrome, Firefox, IE, Safari

Docker
Linux
macOS

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

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

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

SQL like support with command line tool

SQL-like query language

via JavaScript builder pattern

yes

with proprietary extensions

APIs and other access methods

Proprietary protocol
RESTful HTTP API

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

C
C#
C++
Java
Python

JavaScript

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

Server-side scripts

Stored procedures

Python

yes

proprietary syntax

Triggers

yes, Notifications (with Streaming only)

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes, optimistic concurrency control

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

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

yes

In-memory capabilities

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

yes

yes, run db with in-memory only mode

yes

using MemoryDB

yes

User concepts

Access control

yes (enterprise version only)

Users with fine-grained authorization concept

no user groups or roles

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More resources

Recent citations in the news

FRTB product of the year: ActiveViam
28 November 2023, Risk.net

provided by Google News

PlanetScale Unveils Distributed MySQL Database Service Based on Vitess
18 May 2021, Datanami

PlanetScale grabs YouTube-developed open-source tech, promises Vitess DBaaS with on-the-fly schema changes
18 May 2021, The Register

Massively Scaling MySQL Using Vitess
19 February 2019, InfoQ.com

With Vitess 4.0, database vendor matures cloud-native platform
13 November 2019, TechTarget

PlanetScale Serves up Vitess-Powered Serverless MySQL
23 November 2021, The New Stack

provided by Google News

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