DBMS > Cloudflare Workers KV vs. Heroic vs. LevelDB vs. TimesTen

System Properties Comparison Cloudflare Workers KV vs. Heroic vs. LevelDB vs. TimesTen

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Editorial information provided by DB-Engines

Name

Description

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

In-Memory RDBMS compatible to Oracle

Primary database model

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

Score	0.39
Rank	#278	Overall
	#39	Key-value stores

Score	0.57
Rank	#250	Overall
	#21	Time Series DBMS

Score	2.75
Rank	#107	Overall
	#19	Key-value stores

Score	1.35
Rank	#165	Overall
	#75	Relational DBMS

Website

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

github.com/spotify/heroic

github.com/google/leveldb

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

developers.cloudflare.com/kv/api

spotify.github.io/heroic

github.com/google/leveldb/blob/main/doc/index.md

docs.oracle.com/database/timesten-18.1

Developer

Cloudflare

Spotify

Google

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2018

2014

2011

1998

Current release

1.23, February 2021

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

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

Java

C++

Server operating systems

hosted

Illumos
Linux
OS X
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

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.

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

yes

APIs and other access methods

HTTP REST
Proprietary protocol

HQL (Heroic Query Language, a JSON-based language)
HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

PL/SQL

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Immediate Consistency

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

yes

by means of logfiles and checkpoints

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

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