DBMS > AlaSQL vs. atoti vs. EXASOL vs. NSDb vs. RocksDB

System Properties Comparison AlaSQL vs. atoti vs. EXASOL vs. NSDb vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

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

Primary database model

Document store
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	0.61
Rank	#243	Overall
	#10	Object oriented DBMS

Score	1.76
Rank	#139	Overall
	#62	Relational DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

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

Website

Technical documentation

github.com/AlaSQL/alasql

docs.atoti.io

www.exasol.com/resources

nsdb.io/Architecture

github.com/facebook/rocksdb/wiki

Developer

Andrey Gershun & Mathias R. Wulff

ActiveViam

Exasol

Facebook, Inc.

Initial release

2014

2000

2017

2013

Current release

9.2.1, May 2024

License

Commercial or Open Source

Open Source

MIT-License

commercial

free versions available

commercial

Open Source

Apache Version 2.0

Open Source

BSD

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

Java, Scala

C++

Server operating systems

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

Linux
macOS

Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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

all fields are automatically indexed

SQL

Support of SQL

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

Multidimensional Expressions (MDX)

yes

SQL-like query language

APIs and other access methods

JavaScript API

.Net
JDBC
ODBC
WebSocket

gRPC
HTTP REST
WebSocket

C++ API
Java API

Supported programming languages

JavaScript

Java
Lua
Python
R

Java
Scala

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

Python

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding, horizontal partitioning

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual 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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

Using Apache Lucene

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

Access rights for users, groups and roles according to SQL-standard

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