DBMS > Apache Drill vs. Databend vs. Geode

System Properties Comparison Apache Drill vs. Databend vs. Geode

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Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

Primary database model

Document store
Relational DBMS

Relational DBMS

Key-value store

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

Score	1.90
Rank	#126	Overall
	#23	Document stores
	#60	Relational DBMS

Score	0.28
Rank	#287	Overall
	#131	Relational DBMS

Score	1.51
Rank	#147	Overall
	#25	Key-value stores

Website

drill.apache.org

github.com/datafuselabs/databend
www.databend.com

geode.apache.org

Technical documentation

drill.apache.org/docs

docs.databend.com

geode.apache.org/docs

Developer

Apache Software Foundation

Databend Labs

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Initial release

2012

2021

2002

Current release

1.20.3, January 2023

1.0.59, April 2023

1.1, February 2017

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2.0

Open Source

Apache Version 2; commercial licenses available as Gemfire

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Rust

Java

Server operating systems

Linux
OS X
Windows

hosted
Linux
macOS

All OS with a Java VM

the JDK (8 or later) is also required

Data scheme

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

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

SQL-like query language (OQL)

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

CLI Client
JDBC
RESTful HTTP API

Java Client API
Memcached protocol
RESTful HTTP API

Supported programming languages

C++

Go
Java
JavaScript (Node.js)
Python
Rust

.Net
All JVM based languages
C++
Groovy
Java
Scala

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

Cache Event Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

yes, on a single node

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

In-memory capabilities

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

Depending on the underlying data source

yes

User concepts

Access control

Depending on the underlying data source

Users with fine-grained authorization concept, user roles

Access rights per client and object definable

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More resources

Recent citations in the news

Apache Drill case study: A tutorial on processing CSV files
9 June 2016, TheServerSide.com

Analyse Kafka messages with SQL queries using Apache Drill
27 September 2019, Towards Data Science

MapR Advances Support for Flexible and High Performance Analytics on JSON and S3 Data with Apache Drill
30 January 2019, Business Wire

Apache Drill Adds New Data Formats
28 March 2022, iProgrammer

Apache Drill Eliminates ETL, Data Transformation for MapR Database
11 April 2016, The New Stack

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9 September 2024, iProgrammer

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24 May 2007, Thomasnet

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This is how much one of the most expensive gems costs at the Tucson gem show
11 February 2024, KGUN 9 Tucson News

Chapter 1. Introduction to Pivotal GemFire In-Memory Data Grid and Apache Geode
15 November 2018, O'Reilly Media

RDBMS and Apache Geode Data Movement: Low Latency ETL Pipeline by Using Cloud-Native Event Driven Microservices
30 June 2018, InfoQ.com

HPE buys query acceleration platform Ampool to boost Ezmeral hybrid cloud analytics
7 July 2021, SiliconANGLE News

HPE acquires Ampool to gain distributed SQL engine
9 July 2021, VentureBeat

provided by Google News

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