DBMS > Apache Impala vs. Cloudflare Workers KV vs. Drizzle vs. RocksDB

System Properties Comparison Apache Impala vs. Cloudflare Workers KV vs. Drizzle vs. RocksDB

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

Analytic DBMS for Hadoop

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

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

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

Primary database model

Secondary database models

Document store

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	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

impala.apache.org

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

rocksdb.org

Technical documentation

impala.apache.org/impala-docs.html

developers.cloudflare.com/kv/api

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Cloudflare

Drizzle project, originally started by Brian Aker

Facebook, Inc.

Initial release

2013

2018

2008

2013

Current release

4.1.0, June 2022

7.2.4, September 2012

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

GNU GPL

Open Source

BSD

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

Linux

hosted

FreeBSD
Linux
OS X

Linux

Data scheme

yes

schema-free

yes

schema-free

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

SQL

Support of SQL

SQL-like DML and DDL statements

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC

HTTP REST
Proprietary protocol

JDBC

C++ API
Java API

Supported programming languages

All languages supporting JDBC/ODBC

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

C
C++
Java
PHP

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Triggers

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Pluggable authentication mechanisms

e.g. LDAP, HTTP

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