DBMS > Apache Drill vs. Dragonfly vs. Google BigQuery vs. Microsoft Access vs. Redis

System Properties Comparison Apache Drill vs. Dragonfly vs. Google BigQuery vs. Microsoft Access vs. Redis

Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

Large scale data warehouse service with append-only tables

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.)

Popular in-memory data platform used as a cache, message broker, and database that can be deployed on-premises, across clouds, and hybrid environments

Redis focuses on performance so most of its design decisions prioritize high performance and very low latencies.

Primary database model

Document store
Relational DBMS

Key-value store

Relational DBMS

Key-value store

Multiple data types and a rich set of operations, as well as configurable data expiration, eviction and persistence

Secondary database models

Document store

with RedisJSON
Graph DBMS

with RedisGraph
Spatial DBMS
Search engine

with RediSearch
Time Series DBMS

with RedisTimeSeries
Vector DBMS

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

Score	2.02
Rank	#124	Overall
	#22	Document stores
	#59	Relational DBMS

Score	0.49
Rank	#261	Overall
	#38	Key-value stores

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	101.16
Rank	#11	Overall
	#8	Relational DBMS

Score	155.94
Rank	#6	Overall
	#1	Key-value stores

Website

drill.apache.org

github.com/dragonflydb/dragonfly
www.dragonflydb.io

cloud.google.com/bigquery

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

redis.com
redis.io

Technical documentation

drill.apache.org/docs

www.dragonflydb.io/docs

cloud.google.com/bigquery/docs

developer.microsoft.com/en-us/access

docs.redis.com/latest/index.html
redis.io/docs

Developer

Apache Software Foundation

DragonflyDB team and community contributors

Google

Microsoft

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Initial release

2012

2023

2010

1992

2009

Current release

1.20.3, January 2023

1.0, March 2023

1902 (16.0.11328.20222), March 2019

7.2.5, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

BSL 1.1

commercial

Bundled with Microsoft Office

Open Source

source-available extensions (modules), commercial licenses for Redis Enterprise

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.

Aiven for Redis: Fully managed in-memory key-value store for all your caching and speedy lookup needs.

Implementation language

C++

Server operating systems

Linux
OS X
Windows

Linux

hosted

Windows

Not a real database server, but making use of DLLs

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Data scheme

schema-free

scheme-free

yes

schema-free

Typing

predefined data types such as float or date

yes

strings, hashes, lists, sets, sorted sets, bit arrays

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

with RediSearch module

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

but not compliant to any SQL standard

with RediSQL module

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

Proprietary protocol

RESP - REdis Serialization Protocol

RESTful HTTP/JSON API

ADO.NET
DAO
ODBC
OLE DB

proprietary protocol

RESP - REdis Serialization Protocol

Supported programming languages

C++

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

Server-side scripts

Stored procedures

user defined functions

Lua

user defined functions

in JavaScript

yes

since Access 2010 using the ACE-engine

Lua; Redis Functions coming in Redis 7 (slides and Github)

Triggers

publish/subscribe channels provide some trigger functionality

yes

since Access 2010 using the ACE-engine

publish/subscribe channels provide some trigger functionality; RedisGears

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Automatic hash-based sharding with support for hash-tags for manual sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

through RedisGears

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Immediate Consistency

Eventual Consistency
Causal consistency can be enabled in Active-Active databases
Strong consistency with Redis Raft
Strong eventual consistency with Active-Active

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of command blocks and scripts

Since BigQuery is designed for querying data

ACID

but no files for transaction logging

Atomic execution of command blocks and scripts and optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

yes

Data access is serialized by the server

Durability

Support for making data persistent

Depending on the underlying data source

yes

but no files for transaction logging

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

In-memory capabilities

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

Depending on the underlying data source

yes

User concepts

Access control

Depending on the underlying data source

Password-based authentication

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

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

Access Control Lists (ACLs): redis.io/docs/management/security/acl
LDAP and Role-Based Access Control (RBAC) for Redis Enterprise
Mutual TLS authentication: redis.io/docs/management/security/encryption
Password-based authentication

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.