DBMS > Google BigQuery vs. RavenDB vs. RisingWave vs. WakandaDB

System Properties Comparison Google BigQuery vs. RavenDB vs. RisingWave vs. WakandaDB

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

Open Source Operational and Transactional Enterprise NoSQL Document Database

A distributed RDBMS for stream processing, wire-compatible with PostgreSQL

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	2.92
Rank	#101	Overall
	#18	Document stores

Score	0.58
Rank	#242	Overall
	#111	Relational DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

cloud.google.com/bigquery

ravendb.net

www.risingwave.com/database

wakanda.github.io

Technical documentation

cloud.google.com/bigquery/docs

ravendb.net/docs

docs.risingwave.com/docs/current/intro

wakanda.github.io/doc

Developer

Google

Hibernating Rhinos

RisingWave Labs

Wakanda SAS

Initial release

2010

2022

2012

Current release

5.4, July 2022

1.2, September 2023

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

Open Source

AGPL version 3, commercial license available

Open Source

Apache Version 2.0

Open Source

AGPLv3, extended commercial license available

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

Rust

C++, JavaScript

Server operating systems

hosted

Linux
macOS
Raspberry Pi
Windows

Docker
Linux
macOS

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Standard SQL-types and JSON

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

SQL

Support of SQL

yes

SQL-like query language (RQL)

yes

APIs and other access methods

RESTful HTTP/JSON API

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

JDBC
PostgreSQL wire protocol

RESTful HTTP API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Go
Java
JavaScript (Node.js)
Python

JavaScript

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

UDFs in Python or Java

yes

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

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Since BigQuery is designed for querying data

ACID, Cluster-wide transaction available

ACID

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

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

Google Cloud Identity & Access Management (IAM)

Authorization levels configured per client per database

Users and Roles

yes

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