DBMS > ArcadeDB vs. Google BigQuery vs. Lovefield vs. XTDB

System Properties Comparison ArcadeDB vs. Google BigQuery vs. Lovefield vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

Fast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewritten

Large scale data warehouse service with append-only tables

Embeddable relational database for web apps written in pure JavaScript

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

Primary database model

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Relational DBMS

Document store

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

Score	0.10
Rank	#358	Overall
	#48	Document stores
	#38	Graph DBMS
	#52	Key-value stores
	#35	Time Series DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

arcadedb.com

cloud.google.com/bigquery

google.github.io/lovefield

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

Technical documentation

docs.arcadedb.com

cloud.google.com/bigquery/docs

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

www.xtdb.com/docs

Developer

Arcade Data

Google

Juxt Ltd.

Initial release

2021

2010

2014

2019

Current release

September 2021

2.1.12, February 2017

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache 2.0

Open Source

MIT License

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

JavaScript

Clojure

Server operating systems

All OS with a Java VM

hosted

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

tested with Chrome, Firefox, IE, Safari

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

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

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 query language, no joins

yes

SQL-like query language

via JavaScript builder pattern

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin

RESTful HTTP/JSON API

HTTP REST
JDBC

Supported programming languages

Java

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

JavaScript

Clojure
Java

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

yes

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID

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, 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

using MemoryDB

User concepts

Access control

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

Google Cloud Identity & Access Management (IAM)

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