DBMS > Bangdb vs. Datomic vs. LokiJS vs. Microsoft Azure Synapse Analytics vs. NSDb

System Properties Comparison Bangdb vs. Datomic vs. LokiJS vs. Microsoft Azure Synapse Analytics vs. NSDb

Editorial information provided by DB-Engines

Name

Description

Converged and high performance database for device data, events, time series, document and graph

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

In-memory JavaScript DBMS

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

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

Primary database model

Document store
Graph DBMS
Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	0.49
Rank	#260	Overall
	#42	Document stores

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Website

bangdb.com

www.datomic.com

github.com/techfort/LokiJS

azure.microsoft.com/services/synapse-analytics

nsdb.io

Technical documentation

docs.bangdb.com

docs.datomic.com

techfort.github.io/LokiJS

docs.microsoft.com/azure/synapse-analytics

nsdb.io/Architecture

Developer

Sachin Sinha, BangDB

Cognitect

Microsoft

Initial release

2012

2014

2016

2017

Current release

BangDB 2.0, October 2021

1.0.7075, December 2023

License

Commercial or Open Source

Open Source

BSD 3

commercial

limited edition free

Open Source

commercial

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

Java, Clojure

JavaScript

C++

Java, Scala

Server operating systems

Linux

All OS with a Java VM

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

hosted

Linux
macOS

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

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

secondary, composite, nested, reverse, geospatial

yes

via views

yes

all fields are automatically indexed

SQL

Support of SQL

SQL like support with command line tool

yes

SQL-like query language

APIs and other access methods

Proprietary protocol
RESTful HTTP API

RESTful HTTP API

JavaScript API

ADO.NET
JDBC
ODBC

gRPC
HTTP REST
WebSocket

Supported programming languages

C
C#
C++
Java
Python

Clojure
Java

JavaScript

C#
Java
PHP

Java
Scala

Server-side scripts

Stored procedures

yes

Transaction Functions

View functions in JavaScript

Transact SQL

Triggers

yes, Notifications (with Streaming only)

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

none

But extensive use of caching in the application peers

none

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

none

But extensive use of caching in the application peers

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Immediate Consistency

none

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

Transaction concepts

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

ACID

atomic operations within a single collection possible

ACID

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

yes

Using Apache Lucene

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes, run db with in-memory only mode

yes

recommended only for testing and development

yes

User concepts

Access control

yes (enterprise version only)

yes

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More resources

DB-Engines blog posts

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