DBMS > Apache Impala vs. Drizzle vs. EventStoreDB vs. RethinkDB vs. XTDB

System Properties Comparison Apache Impala vs. Drizzle vs. EventStoreDB vs. RethinkDB vs. XTDB

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

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

Industrial-strength, open-source database solution built from the ground up for event sourcing.

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Relational DBMS

Event Store

Document store

Secondary database models

Document store

Spatial DBMS

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	1.10
Rank	#179	Overall
	#1	Event Stores

Score	2.74
Rank	#105	Overall
	#19	Document stores

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

impala.apache.org

www.eventstore.com

rethinkdb.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

impala.apache.org/impala-docs.html

developers.eventstore.com

rethinkdb.com/docs

www.xtdb.com/docs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Drizzle project, originally started by Brian Aker

Event Store Limited

The Linux Foundation

since July 2017

Juxt Ltd.

Initial release

2013

2008

2012

2009

2019

Current release

4.1.0, June 2022

7.2.4, September 2012

21.2, February 2021

2.4.1, August 2020

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

GNU GPL

Open Source

Apache Version 2

Open Source

MIT License

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Clojure

Server operating systems

Linux

FreeBSD
Linux
OS X

Linux
Windows

Linux
OS X
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

yes, extensible-data-notation format

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

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC
ODBC

JDBC

HTTP REST
JDBC

Supported programming languages

All languages supporting JDBC/ODBC

C
C++
Java
PHP

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

Clojure
Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Triggers

hooks for callbacks inside the server can be used.

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

Sharding

range based

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication
Source-replica replication

Source-replica replication

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Pluggable authentication mechanisms

e.g. LDAP, HTTP

yes

users and table-level permissions

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More resources

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Recent citations in the news

Apache Impala 4 Supports Operator Multi-Threading
29 July 2021, iProgrammer

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

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14 July 2022, Datanami

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

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12 March 2017, Uber

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15 August 2023, Open Source For You

How to Use RethinkDB with Node.js Applications — SitePoint
16 December 2015, SitePoint

Stripe acquires team behind NoSQL database startup RethinkDB
5 October 2016, VentureBeat

RethinkDB is dead, and MongoDB isn't what killed it
24 January 2017, TechRepublic

How to deploy RethinkDB using Docker
14 February 2018, Packt Hub

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