DBMS > Amazon CloudSearch vs. Databricks vs. Google BigQuery vs. jBASE vs. Postgres-XL

System Properties Comparison Amazon CloudSearch vs. Databricks vs. Google BigQuery vs. jBASE vs. Postgres-XL

Editorial information provided by DB-Engines

Name

Description

A hosted search engine service by Amazon with the data stored in Amazons cloud

The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.

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

Primary database model

Search engine

Document store
Relational DBMS

Relational DBMS

Multivalue DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	1.81
Rank	#137	Overall
	#12	Search engines

Score	81.08
Rank	#15	Overall
	#2	Document stores
	#10	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	1.49
Rank	#156	Overall
	#3	Multivalue DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Website

aws.amazon.com/cloudsearch

www.databricks.com

cloud.google.com/bigquery

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

www.postgres-xl.org

Technical documentation

docs.aws.amazon.com/cloudsearch

docs.databricks.com

cloud.google.com/bigquery/docs

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

www.postgres-xl.org/documentation

Developer

Amazon

Databricks

Google

Rocket Software (formerly Zumasys)

Initial release

2012

2013

2010

1991

2014

since 2012, originally named StormDB

Current release

5.7

10 R1, October 2018

License

Commercial or Open Source

commercial

Open Source

Mozilla public license

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

Server operating systems

hosted

AIX
Linux
Windows

Linux
macOS

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

optional

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.

yes

XML type, but no XML query functionality

Secondary indexes

yes

all search fields are automatically indexed

yes

SQL

Support of SQL

with Databricks SQL

yes

Embedded SQL for jBASE in BASIC

yes

distributed, parallel query execution

APIs and other access methods

HTTP API

JDBC
ODBC
RESTful HTTP API

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

Supported programming languages

Python
R
Scala

.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

Server-side scripts

Stored procedures

user defined functions and aggregates

user defined functions

in JavaScript

yes

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

yes

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

ACID

Since BigQuery is designed for querying data

ACID

MVCC

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

authentication via encrypted signatures

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

More information provided by the system vendor

Specific characteristics

Supported database models : In addition to the Document store and Relational DBMS...
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