DBMS > AlaSQL vs. Apache Druid vs. Microsoft SQL Server vs. PlanetScale vs. Warp 10

System Properties Comparison AlaSQL vs. Apache Druid vs. Microsoft SQL Server vs. PlanetScale vs. Warp 10

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

Microsofts flagship relational DBMS

Scalable, distributed, serverless MySQL database platform built on top of Vitess

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

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Spatial DBMS

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

Score	0.46
Rank	#260	Overall
	#40	Document stores
	#121	Relational DBMS

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	1.59
Rank	#151	Overall
	#70	Relational DBMS

Score	0.07
Rank	#349	Overall
	#32	Time Series DBMS

Website

alasql.org

druid.apache.org

www.microsoft.com/en-us/sql-server

planetscale.com

www.warp10.io

Technical documentation

github.com/AlaSQL/alasql

druid.apache.org/docs/latest/design

learn.microsoft.com/en-US/sql/sql-server

planetscale.com/docs

www.warp10.io/content/02_Getting_started

Developer

Andrey Gershun & Mathias R. Wulff

Apache Software Foundation and contributors

Microsoft

PlanetScale

SenX

Initial release

2014

2012

1989

2020

2015

Current release

29.0.1, April 2024

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache license v2

commercial

restricted free version is available

commercial

Open Source

Apache License 2.0

Cloud-based only

Only available as a cloud service

yes

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Implementation language

JavaScript

Java

C++

Java

Server operating systems

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

Linux
OS X
Unix

Linux
Windows

Docker
Linux
macOS

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.

yes

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

with proprietary extensions

APIs and other access methods

JavaScript API

JDBC
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

ADO.NET
JDBC
MySQL protocol
ODBC

HTTP API
Jupyter
WebSocket

Supported programming languages

JavaScript

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

proprietary syntax

yes

WarpScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

manual/auto, time-based

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes, via HDFS, S3 or other storage engines

yes, but depending on the SQL-Server Edition

Multi-source replication
Source-replica replication

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

Eventual Consistency across shards
Immediate Consistency within a shard

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

yes

only for local storage and DOM-storage

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

Users with fine-grained authorization concept

no user groups or roles

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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