DBMS > Amazon Redshift vs. Badger vs. LevelDB vs. Microsoft Azure Synapse Analytics vs. RocksDB

System Properties Comparison Amazon Redshift vs. Badger vs. LevelDB vs. Microsoft Azure Synapse Analytics vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

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

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

aws.amazon.com/redshift

github.com/dgraph-io/badger

github.com/google/leveldb

azure.microsoft.com/services/synapse-analytics

rocksdb.org

Technical documentation

docs.aws.amazon.com/redshift

godoc.org/github.com/dgraph-io/badger

github.com/google/leveldb/blob/main/doc/index.md

docs.microsoft.com/azure/synapse-analytics

github.com/facebook/rocksdb/wiki

Developer

Amazon (based on PostgreSQL)

DGraph Labs

Google

Microsoft

Facebook, Inc.

Initial release

2012

2017

2011

2016

2013

Current release

1.23, February 2021

8.11.4, April 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

BSD

commercial

Open Source

BSD

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++

Server operating systems

hosted

BSD
Linux
OS X
Solaris
Windows

Illumos
Linux
OS X
Windows

hosted

Linux

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC

C++ API
Java API

Supported programming languages

All languages supporting JDBC/ODBC

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C#
Java
PHP

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

Transact SQL

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding, horizontal partitioning

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

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

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

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

yes

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