DBMS > IBM Db2 Event Store vs. Microsoft Access vs. MongoDB vs. Rockset vs. Sqrrl

System Properties Comparison IBM Db2 Event Store vs. Microsoft Access vs. MongoDB vs. Rockset vs. Sqrrl

Editorial information provided by DB-Engines

Name

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.

Description

Distributed Event Store optimized for Internet of Things use cases

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure

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

Adaptable, secure NoSQL built on Apache Accumulo

Primary database model

Event Store
Time Series DBMS

Relational DBMS

Document store

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Spatial DBMS
Search engine

integrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS

Time Series Collections introduced in Release 5.0
Vector DBMS

currently available in the MongoDB Atlas cloud service only

Relational DBMS
Search engine

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

Score	0.27
Rank	#309	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	101.16
Rank	#11	Overall
	#8	Relational DBMS

Score	421.08
Rank	#5	Overall
	#1	Document stores

Score	0.82
Rank	#212	Overall
	#36	Document stores

Website

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

www.microsoft.com/en-us/microsoft-365/access

www.mongodb.com

rockset.com

sqrrl.com

Technical documentation

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

developer.microsoft.com/en-us/access

www.mongodb.com/docs/manual

docs.rockset.com

Developer

IBM

Microsoft

MongoDB, Inc

Rockset

Amazon

originally Sqrrl Data, Inc.

Initial release

2017

1992

2009

2019

2012

Current release

2.0

1902 (16.0.11328.20222), March 2019

6.0.7, June 2023

License

Commercial or Open Source

commercial

free developer edition available

commercial

Bundled with Microsoft Office

Open Source

MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.

commercial

Cloud-based only

Only available as a cloud service

MongoDB available as DBaaS (MongoDB Atlas)

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C and C++

C++

Java

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

Windows

Not a real database server, but making use of DLLs

Linux
OS X
Solaris
Windows

hosted

Linux

Data scheme

yes

schema-free

Although schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, decimal, boolean, date, object_id, geospatial

dynamic typing

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.

ingestion from XML files supported

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

yes

but not compliant to any SQL standard

Read-only SQL queries via the MongoDB Atlas SQL Interface

Read-only SQL queries, including JOINs

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

ADO.NET
DAO
ODBC
OLE DB

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

HTTP REST

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

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

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

Actionscript

unofficial driver
C
C#
C++
Clojure

unofficial driver
ColdFusion

unofficial driver
D

unofficial driver
Dart

unofficial driver
Delphi

unofficial driver
Erlang
Go
Groovy

unofficial driver
Haskell
Java
JavaScript
Kotlin
Lisp

unofficial driver
Lua

unofficial driver
MatLab

unofficial driver
Perl
PHP
PowerShell

unofficial driver
Prolog

unofficial driver
Python
R

unofficial driver
Ruby
Rust
Scala
Smalltalk

unofficial driver
Swift

Go
Java
JavaScript (Node.js)
Python

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

Server-side scripts

Stored procedures

yes

since Access 2010 using the ACE-engine

JavaScript

Triggers

yes

since Access 2010 using the ACE-engine

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Partitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.

Automatic sharding

Sharding

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

none

Multi-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication

yes

selectable replication factor

making use of Hadoop

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Eventual Consistency

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

Foreign keys

Referential integrity

yes

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

ACID

but no files for transaction logging

Multi-document ACID Transactions with snapshot isolation

Atomic updates per row, document, or graph entity

Concurrency

Support for concurrent manipulation of data

No - written data is immutable

yes

Durability

Support for making data persistent

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

yes

but no files for transaction logging

yes

optional, enabled by default

yes

In-memory capabilities

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

yes

In-memory storage engine introduced with MongoDB version 3.2

User concepts

Access control

fine grained access rights according to SQL-standard

a simple user-level security was built in till version Access 2003

Access rights for users and roles

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

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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