DBMS > AlaSQL vs. Apache Druid vs. OpenMLDB vs. RocksDB vs. SwayDB

System Properties Comparison AlaSQL vs. Apache Druid vs. OpenMLDB vs. RocksDB vs. SwayDB

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 open-source machine learning database that provides a feature platform for training and inference

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

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Document store
Relational DBMS

Relational DBMS
Time Series DBMS

Time Series DBMS

Key-value store

Secondary database models

Relational DBMS

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

Score	0.51
Rank	#256	Overall
	#40	Document stores
	#118	Relational DBMS

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

Score	0.10
Rank	#359	Overall
	#36	Time Series DBMS

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

Score	0.04
Rank	#387	Overall
	#61	Key-value stores

Website

Technical documentation

github.com/AlaSQL/alasql

druid.apache.org/docs/latest/design

openmldb.ai/docs/zh/main

github.com/facebook/rocksdb/wiki

Developer

Andrey Gershun & Mathias R. Wulff

Apache Software Foundation and contributors

4 Paradigm Inc.

Facebook, Inc.

Simer Plaha

Initial release

2014

2012

2020

2013

2018

Current release

29.0.1, April 2024

2024-2 February 2024

9.2.1, May 2024

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache license v2

Open Source

BSD

Open Source

GNU Affero GPL V3.0

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, Scala

C++

Scala

Server operating systems

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

Linux
OS X
Unix

Linux

Data scheme

schema-free

yes

schema-less columns are supported

Fixed schema

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

JDBC
SQLAlchemy

C++ API
Java API

Supported programming languages

JavaScript

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C++
Go
Java
Python
Scala

C
C++
Go
Java
Perl
Python
Ruby

Java
Kotlin
Scala

Server-side scripts

Stored procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

manual/auto, time-based

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes, via HDFS, S3 or other storage engines

Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

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

yes

only for local storage and DOM-storage

yes

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

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

fine grained access rights according to SQL-standard

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.