DBMS > Apache Impala vs. Cloudflare Workers KV vs. Oracle vs. PouchDB vs. Transbase

System Properties Comparison Apache Impala vs. Cloudflare Workers KV vs. Oracle vs. PouchDB vs. Transbase

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

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

Widely used RDBMS

JavaScript DBMS with an API inspired by CouchDB

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Secondary database models

Document store

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

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

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

impala.apache.org

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

www.oracle.com/database

pouchdb.com

www.transaction.de/en/products/transbase.html

Technical documentation

impala.apache.org/impala-docs.html

developers.cloudflare.com/kv/api

docs.oracle.com/en/database

pouchdb.com/guides

www.transaction.de/en/products/transbase/features.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Cloudflare

Oracle

Apache Software Foundation

Transaction Software GmbH

Initial release

2013

2018

1980

2012

1987

Current release

4.1.0, June 2022

23c, September 2023

7.1.1, June 2019

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

restricted free version is available

Open Source

commercial

free development 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

C++

C and C++

JavaScript

C and C++

Server operating systems

Linux

hosted

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

server-less, requires a JavaScript environment (browser, Node.js)

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

schema-free

yes

Schemaless in JSON and XML columns

schema-free

yes

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

Secondary indexes

yes

via views

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

with proprietary extensions

yes

APIs and other access methods

JDBC
ODBC

HTTP REST
Proprietary protocol

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

HTTP REST

only for PouchDB Server
JavaScript API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

All languages supporting JDBC/ODBC

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

JavaScript

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

PL/SQL

also stored procedures in Java possible

View functions in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

Multi-source replication
Source-replica replication

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

can be realized in PL/SQL

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

isolation level can be parameterized

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard

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