DBMS > Cloudflare Workers KV vs. Fujitsu Enterprise Postgres vs. Microsoft SQL Server vs. Rockset vs. Teradata Aster

System Properties Comparison Cloudflare Workers KV vs. Fujitsu Enterprise Postgres vs. Microsoft SQL Server vs. Rockset 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

A global, low-latency, key-value store for applications on Cloudflare with exceptionally high read volumes and low-latency.

Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.

Microsofts flagship relational DBMS

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Platform for big data analytics on multistructured data sources and types

Primary database model

Secondary database models

Document store
Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

Relational DBMS
Search engine

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

Score	0.32
Rank	#283	Overall
	#40	Key-value stores

Score	0.31
Rank	#285	Overall
	#129	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.79
Rank	#211	Overall
	#35	Document stores

Website

www.cloudflare.com/developer-platform/workers-kv

www.postgresql.fastware.com

www.microsoft.com/en-us/sql-server

rockset.com

Technical documentation

developers.cloudflare.com/kv/api

www.postgresql.fastware.com/product-manuals

learn.microsoft.com/en-US/sql/sql-server

docs.rockset.com

Developer

Cloudflare

PostgreSQL Global Development Group, Fujitsu Australia Software Technology

Microsoft

Rockset

Teradata

Initial release

2018

1989

2019

2005

Current release

Fujitsu Enterprise Postgres 14, January 2022

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Server operating systems

hosted

Linux
Windows

hosted

Linux

Data scheme

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

dynamic typing

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

ingestion from XML files supported

yes

in Aster File Store

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

yes

Read-only SQL queries, including JOINs

yes

APIs and other access methods

HTTP REST
Proprietary protocol

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

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

HTTP REST

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

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

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Go
Java
JavaScript (Node.js)
Python

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

user defined functions

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

R packages

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

partitioning by range, list and by hash

tables can be distributed across several files (horizontal partitioning); sharding through federation

Automatic sharding

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes, but depending on the SQL-Server Edition

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

Eventual Consistency

Immediate Consistency

Eventual 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

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

fine grained access rights according to SQL-standard

Access rights for users and organizations can be defined via Rockset console

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

100% compatible with community PostgreSQL
» more

Competitive advantages

Built-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more

Typical application scenarios

Transactional payments applications, reporting and mixed workloads.
» more

Market metrics

Over 30 years experience in database technology. Over 20 years in Postgres development...
» more

Licensing and pricing models

Core based licensing
» more

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