DBMS > Cloudflare Workers KV vs. Oracle vs. Tarantool vs. Yaacomo

System Properties Comparison Cloudflare Workers KV vs. Oracle vs. Tarantool vs. Yaacomo

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Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is 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.

Widely used RDBMS

In-memory computing platform with a flexible data schema for efficiently building high-performance applications

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Key-value store

Relational DBMS

Document store
Key-value store
Relational DBMS

Relational DBMS

Secondary database models

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

Spatial DBMS

with Tarantool/GIS extension

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

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

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	1.72
Rank	#144	Overall
	#25	Document stores
	#25	Key-value stores
	#66	Relational DBMS

Website

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

www.oracle.com/database

www.tarantool.io

yaacomo.com

Technical documentation

developers.cloudflare.com/kv/api

docs.oracle.com/en/database

www.tarantool.io/en/doc

Developer

Cloudflare

Oracle

Q2WEB GmbH

Initial release

2018

1980

2008

2009

Current release

23c, September 2023

2.10.0, May 2022

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise

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 and C++

Server operating systems

hosted

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

BSD
Linux
macOS

Android
Linux
Windows

Data scheme

schema-free

yes

Schemaless in JSON and XML columns

Flexible data schema: relational definition for tables with ability to store json-like documents in columns

yes

Typing

predefined data types such as float or date

yes

string, double, decimal, uuid, integer, blob, boolean, datetime

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

SQL

Support of SQL

yes

with proprietary extensions

Full-featured ANSI SQL support

yes

APIs and other access methods

HTTP REST
Proprietary protocol

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Open binary protocol

JDBC
ODBC

Supported programming languages

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

C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust

Server-side scripts

Stored procedures

PL/SQL

also stored procedures in Java possible

Lua, C and SQL stored procedures

Triggers

yes

yes, before/after data modification events, on replication events, client session events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Casual consistency across sharding partitions
Eventual consistency within replicaset partition

when using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition

when using Raft

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

ACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, cooperative multitasking

yes

Durability

Support for making data persistent

yes

yes, write ahead logging

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, full featured in-memory storage engine with persistence

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

fine grained access rights according to SQL-standard

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