DBMS > 4D vs. Google Cloud Bigtable vs. Microsoft Azure AI Search vs. RocksDB vs. Teradata Aster

System Properties Comparison 4D vs. Google Cloud Bigtable vs. Microsoft Azure AI Search vs. RocksDB vs. Teradata Aster

Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

Application development environment with integrated database management system

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Search-as-a-service for web and mobile app development

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Platform for big data analytics on multistructured data sources and types

Primary database model

Relational DBMS

Key-value store
Wide column store

Search engine

Key-value store

Relational DBMS

Secondary database models

Vector DBMS

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

Score	2.47
Rank	#110	Overall
	#54	Relational DBMS

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	5.52
Rank	#59	Overall
	#6	Search engines

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

www.4d.com

cloud.google.com/bigtable

azure.microsoft.com/en-us/services/search

rocksdb.org

Technical documentation

developer.4d.com

cloud.google.com/bigtable/docs

learn.microsoft.com/en-us/azure/search

github.com/facebook/rocksdb/wiki

Developer

4D, Inc

Google

Microsoft

Facebook, Inc.

Teradata

Initial release

1984

2015

2013

2005

Current release

v20, April 2023

9.2.1, May 2024

License

Commercial or Open Source

commercial

Open Source

BSD

commercial

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

C++

Server operating systems

OS X
Windows

hosted

Linux

Data scheme

yes

schema-free

yes

schema-free

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

defined schema within the relational store; partial schema or schema free in the Aster File Store

Typing

predefined data types such as float or date

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

in Aster File Store

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

yes

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

RESTful HTTP API

C++ API
Java API

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

4D proprietary IDE
PHP

C#
C++
Go
Java
JavaScript (Node.js)
Python

C#
Java
JavaScript
Python

C
C++
Go
Java
Perl
Python
Ruby

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

yes

R packages

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Internal replication in Colossus, and regional replication between two clusters in different zones

yes

Implicit feature of the cloud service

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic single-row operations

yes

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

Users and groups

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

yes

using Azure authentication

fine grained access rights according to SQL-standard

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