DBMS > AlaSQL vs. Apache Druid vs. DuckDB vs. Warp 10

System Properties Comparison AlaSQL vs. Apache Druid vs. DuckDB vs. Warp 10

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

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

An embeddable, in-process, column-oriented SQL OLAP RDBMS

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Document store
Relational DBMS

Relational DBMS
Time Series DBMS

Relational DBMS

Time Series DBMS

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

Score	0.42
Rank	#264	Overall
	#42	Document stores
	#122	Relational DBMS

Score	2.85
Rank	#96	Overall
	#50	Relational DBMS
	#6	Time Series DBMS

Score	5.61
Rank	#60	Overall
	#34	Relational DBMS

Score	0.06
Rank	#351	Overall
	#35	Time Series DBMS

Website

Technical documentation

github.com/AlaSQL/alasql

druid.apache.org/docs/latest/design

duckdb.org/docs

www.warp10.io/content/02_Getting_started

Developer

Andrey Gershun & Mathias R. Wulff

Apache Software Foundation and contributors

SenX

Initial release

2014

2012

2018

2015

Current release

30.0.0, June 2024

1.0.0, June 2024

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache license v2

Open Source

MIT License

Open Source

Apache License 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

JavaScript

Java

C++

Java

Server operating systems

server-less, requires a JavaScript environment (browser, Node.js)

Linux
OS X
Unix

server-less

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-less columns are supported

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

Close to SQL99, but no user access control, stored procedures and host language bindings.

SQL for querying

yes

APIs and other access methods

JavaScript API

JDBC
RESTful HTTP/JSON API

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

HTTP API
Jupyter
WebSocket

Supported programming languages

JavaScript

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C
C#

3rd party driver
C++
Crystal

3rd party driver
Go

3rd party driver
Java
Lisp

3rd party driver
Python
R
Ruby

3rd party driver
Rust
Swift
Zig

3rd party driver

Server-side scripts

Stored procedures

yes

WarpScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

manual/auto, time-based

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes, via HDFS, S3 or other storage engines

none

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

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

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

Mandatory use of cryptographic tokens, containing fine-grained authorizations

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

HarperDB - How and Why We Built It From The Ground Up on NodeJS
28 February 2021, hackernoon.com

Multi faceted data exploration in the browser using Leaflet and amCharts
3 May 2020, Towards Data Science

provided by Google News

Imply Announces the Availability of Imply Polaris, a Database-as-a-Service Built from Apache Druid, on Microsoft Azure
26 June 2024, businesswire.com

'Lucifer' Botnet Turns Up the Heat on Apache Hadoop Servers
21 February 2024, Dark Reading

New DDoS malware Attacking Apache big-data stack, Hadoop, & Druid Servers
26 February 2024, GBHackers

Apache® Druid Wins Best Big Data Product in the 2023 BigDATAwire Readers’ Choice Awards
26 January 2024, businesswire.com

Apache Druid Takes Its Place In The Pantheon Of Databases
16 June 2022, The Next Platform

provided by Google News

My First Billion (of Rows) in DuckDB
1 May 2024, Towards Data Science

TigerEye Open Sources DuckDB.dart
15 August 2024, Datanami

Unleashing Postgres for Analytics With DuckDB Integration
24 July 2024, The New Stack

DuckDB: The tiny but powerful analytics database
15 May 2024, InfoWorld

Reading PCAP Files (Directly) With DuckDB
26 August 2024, Security Boulevard

provided by Google News

Launched Just A Year Ago, Open-Source Scality S3 Server Gains Extraordinary Momentum As It Simplifies The Life Of Developers
28 June 2017, PR Newswire

provided by Google News

Share this page