DBMS > Apache Drill vs. Apache Druid vs. HarperDB vs. RocksDB vs. Snowflake

System Properties Comparison Apache Drill vs. Apache Druid vs. HarperDB vs. RocksDB vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

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

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

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

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Document store
Relational DBMS

Relational DBMS
Time Series DBMS

Document store

Key-value store

Relational DBMS

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

Score	2.02
Rank	#124	Overall
	#22	Document stores
	#59	Relational DBMS

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	0.60
Rank	#244	Overall
	#38	Document stores

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

Technical documentation

drill.apache.org/docs

druid.apache.org/docs/latest/design

docs.harperdb.io/docs

github.com/facebook/rocksdb/wiki

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation

Apache Software Foundation and contributors

HarperDB

Facebook, Inc.

Snowflake Computing Inc.

Initial release

2012

2017

2013

2014

Current release

1.20.3, January 2023

29.0.1, April 2024

3.1, August 2021

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache license v2

commercial

free community edition available

Open Source

BSD

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

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Implementation language

Java

Node.js

C++

Server operating systems

Linux
OS X
Windows

Linux
OS X
Unix

Linux
OS X

Linux

hosted

Data scheme

schema-free

yes

schema-less columns are supported

dynamic schema

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

JSON data types

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

SQL SELECT statement is SQL:2003 compliant

SQL for querying

SQL-like data manipulation statements

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

JDBC
RESTful HTTP/JSON API

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

C++ API
Java API

CLI Client
JDBC
ODBC

Supported programming languages

C++

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

C
C++
Go
Java
Perl
Python
Ruby

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

Custom Functions

since release 3.1

user defined functions

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

A table resides as a whole on one (or more) nodes in a cluster

horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes

the nodes on which a table resides can be defined

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

yes, using LMDB

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Access rights for users and roles

Users with fine-grained authorization concept, user roles and pluggable authentication

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