DBMS > AlaSQL vs. Brytlyt vs. Elasticsearch vs. Microsoft SQL Server vs. Warp 10

System Properties Comparison AlaSQL vs. Brytlyt vs. Elasticsearch vs. Microsoft SQL Server vs. Warp 10

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

Microsofts flagship relational DBMS

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

Primary database model

Document store
Relational DBMS

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Document store
Graph DBMS
Spatial 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	0.38
Rank	#276	Overall
	#127	Relational DBMS

Score	132.83
Rank	#7	Overall
	#1	Search engines

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.14
Rank	#344	Overall
	#32	Time Series DBMS

Website

alasql.org

brytlyt.io

www.elastic.co/elasticsearch

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

www.warp10.io

Technical documentation

github.com/AlaSQL/alasql

docs.brytlyt.io

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

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

www.warp10.io/content/02_Getting_started

Developer

Andrey Gershun & Mathias R. Wulff

Brytlyt

Elastic

Microsoft

SenX

Initial release

2014

2016

2010

1989

2015

Current release

5.0, August 2023

8.6, January 2023

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

MIT-License

commercial

Open Source

Elastic License

commercial

restricted free version is available

Open Source

Apache License 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

JavaScript

C, C++ and CUDA

Java

C++

Java

Server operating systems

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

Linux
OS X
Windows

All OS with a Java VM

Linux
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

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

specific XML-type available, but no XML query functionality.

yes

Secondary indexes

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

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

yes

SQL-like query language

yes

APIs and other access methods

JavaScript API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Java API
RESTful HTTP/JSON API

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

HTTP API
Jupyter
WebSocket

Supported programming languages

JavaScript

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

yes

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

yes

WarpScript

Triggers

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

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

Source-replica replication

yes

yes, but depending on the SQL-Server Edition

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

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

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

Memcached and Redis integration

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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