DBMS > FeatureBase vs. IBM Db2 Event Store vs. Microsoft SQL Server vs. PouchDB vs. Rockset

System Properties Comparison FeatureBase vs. IBM Db2 Event Store vs. Microsoft SQL Server vs. PouchDB vs. Rockset

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.

Distributed Event Store optimized for Internet of Things use cases

Microsofts flagship relational DBMS

JavaScript DBMS with an API inspired by CouchDB

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Primary database model

Relational DBMS

Event Store
Time Series DBMS

Relational DBMS

Document store

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Relational DBMS
Search engine

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

Score	0.22
Rank	#309	Overall
	#139	Relational DBMS

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	0.79
Rank	#211	Overall
	#35	Document stores

Website

www.featurebase.com

www.ibm.com/products/db2-event-store

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

pouchdb.com

rockset.com

Technical documentation

docs.featurebase.com

www.ibm.com/docs/en/db2-event-store

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

pouchdb.com/guides

docs.rockset.com

Developer

Molecula and Pilosa Open Source Contributors

IBM

Microsoft

Apache Software Foundation

Rockset

Initial release

2017

1989

2012

2019

Current release

2022, May 2022

2.0

SQL Server 2022, November 2022

7.1.1, June 2019

License

Commercial or Open Source

commercial

free developer edition available

commercial

restricted free version is available

Open Source

commercial

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 and C++

C++

JavaScript

C++

Server operating systems

Linux
macOS

Linux

Linux, macOS, Windows for the developer addition

Linux
Windows

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

hosted

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

dynamic typing

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

ingestion from XML files supported

Secondary indexes

yes

via views

all fields are automatically indexed

SQL

Support of SQL

SQL queries

yes

through the embedded Spark runtime

yes

Read-only SQL queries, including JOINs

APIs and other access methods

gRPC
JDBC
Kafka Connector
ODBC

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

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

HTTP REST

only for PouchDB Server
JavaScript API

HTTP REST

Supported programming languages

Java
Python

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

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

JavaScript

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

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

View functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Sharding

with a proxy-based framework, named couchdb-lounge

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Active-active shard replication

yes, but depending on the SQL-Server Edition

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

Durability

Support for making data persistent

yes, using Linux fsync

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

yes

by using IndexedDB, WebSQL or LevelDB as backend

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

fine grained access rights according to SQL-standard

Access rights for users and organizations can be defined via Rockset console

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