DBMS > Google BigQuery vs. jBASE vs. Postgres-XL vs. Realm vs. RisingWave

System Properties Comparison Google BigQuery vs. jBASE vs. Postgres-XL vs. Realm vs. RisingWave

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

A robust multi-value DBMS comprising development tools and middleware

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

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

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	1.41
Rank	#159	Overall
	#3	Multivalue DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	0.58
Rank	#242	Overall
	#111	Relational DBMS

Website

cloud.google.com/bigquery

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

www.postgres-xl.org

realm.io

www.risingwave.com/database

Technical documentation

cloud.google.com/bigquery/docs

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

www.postgres-xl.org/documentation

realm.io/docs

docs.risingwave.com/docs/current/intro

Developer

Google

Rocket Software (formerly Zumasys)

Realm, acquired by MongoDB in May 2019

RisingWave Labs

Initial release

2010

1991

2014

since 2012, originally named StormDB

2014

2022

Current release

5.7

10 R1, October 2018

1.2, September 2023

License

Commercial or Open Source

commercial

Open Source

Mozilla public license

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Rust

Server operating systems

hosted

AIX
Linux
Windows

Linux
macOS

Android
Backend: server-less
iOS
Windows

Docker
Linux
macOS

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

optional

yes

Standard SQL-types and JSON

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.

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

Embedded SQL for jBASE in BASIC

yes

distributed, parallel query execution

yes

APIs and other access methods

RESTful HTTP/JSON API

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC
PostgreSQL wire protocol

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
Basic
Jabbascript
Java

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

.Net
Java

with Android only
Objective-C
React Native
Swift

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

user defined functions

runs within the applications so server-side scripts are unnecessary

UDFs in Python or Java

Triggers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

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

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

MVCC

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

In-Memory realm

yes

User concepts

Access control

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

Google Cloud Identity & Access Management (IAM)

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

yes

Users and Roles

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