DBMS > FeatureBase vs. JaguarDB vs. Microsoft Azure Cosmos DB vs. Realm vs. searchxml

System Properties Comparison FeatureBase vs. JaguarDB vs. Microsoft Azure Cosmos DB vs. Realm vs. searchxml

Editorial information provided by DB-Engines

Name

Description

Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.

Performant, highly scalable DBMS for AI and IoT applications

Globally distributed, horizontally scalable, multi-model database service

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Relational DBMS

Key-value store
Vector DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Document store

Native XML DBMS
Search engine

Secondary database models

Spatial DBMS

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

Score	0.31
Rank	#292	Overall
	#135	Relational DBMS

Score	0.06
Rank	#381	Overall
	#59	Key-value stores
	#14	Vector DBMS

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	7.41
Rank	#52	Overall
	#8	Document stores

Score	0.03
Rank	#390	Overall
	#7	Native XML DBMS
	#24	Search engines

Website

www.featurebase.com

www.jaguardb.com

azure.microsoft.com/services/cosmos-db

realm.io

www.searchxml.net/category/products

Technical documentation

docs.featurebase.com

www.jaguardb.com/support.html

learn.microsoft.com/azure/cosmos-db

realm.io/docs

www.searchxml.net/support/handouts

Developer

Molecula and Pilosa Open Source Contributors

DataJaguar, Inc.

Microsoft

Realm, acquired by MongoDB in May 2019

informationpartners gmbh

Initial release

2017

2015

2014

2015

Current release

2022, May 2022

3.3 July 2023

1.0

License

Commercial or Open Source

commercial

Open Source

GPL V3.0

commercial

Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

the server part. Clients available in other languages

C++

Server operating systems

Linux
macOS

Linux

hosted

Android
Backend: server-less
iOS
Windows

Windows

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL queries

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

SQL-like query language

APIs and other access methods

gRPC
JDBC
Kafka Connector
ODBC

JDBC
ODBC

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

Java
Python

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

.Net
Java

with Android only
Objective-C
React Native
Swift

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

JavaScript

runs within the applications so server-side scripts are unnecessary

yes

on the application server

Triggers

JavaScript

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

yes

Implicit feature of the cloud service

none

yes

sychronisation to multiple collections

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

Multi-item ACID transactions with snapshot isolation within a partition

ACID

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes, using Linux fsync

yes

In-memory capabilities

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

yes

In-Memory realm

User concepts

Access control

rights management via user accounts

Access rights can be defined down to the item level

yes

Domain, group and role-based access control at the document level and for application services

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