DBMS > Microsoft Azure Table Storage vs. ReductStore vs. Rockset vs. Transbase vs. XTDB

System Properties Comparison Microsoft Azure Table Storage vs. ReductStore vs. Rockset vs. Transbase vs. XTDB

Editorial information provided by DB-Engines

Name

Description

A Wide Column Store for rapid development using massive semi-structured datasets

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

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

A resource-optimized, high-performance, universally applicable RDBMS

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Secondary database models

Relational DBMS
Search engine

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

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	0.05
Rank	#384	Overall
	#44	Time Series DBMS

Score	0.82
Rank	#212	Overall
	#36	Document stores

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

azure.microsoft.com/en-us/services/storage/tables

github.com/reductstore
www.reduct.store

rockset.com

www.transaction.de/en/products/transbase.html

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

www.reduct.store/docs

docs.rockset.com

www.transaction.de/en/products/transbase/features.html

www.xtdb.com/docs

Developer

Microsoft

ReductStore LLC

Rockset

Transaction Software GmbH

Juxt Ltd.

Initial release

2012

2023

2019

1987

2019

Current release

1.9, March 2024

Transbase 8.3, 2022

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

Business Source License 1.1

commercial

free development license

Open Source

MIT License

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++, Rust

C++

C and C++

Clojure

Server operating systems

hosted

Docker
Linux
macOS
Windows

hosted

FreeBSD
Linux
macOS
Solaris
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

dynamic typing

yes

yes, extensible-data-notation format

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

all fields are automatically indexed

yes

SQL

Support of SQL

Read-only SQL queries, including JOINs

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

RESTful HTTP API

HTTP API

HTTP REST

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP REST
JDBC

Supported programming languages

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

C++
JavaScript (Node.js)
Python
Rust

Go
Java
JavaScript (Node.js)
Python

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Clojure
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Automatic sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

yes

Source-replica replication

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

optimistic locking

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

User concepts

Access control

Access rights based on private key authentication or shared access signatures

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

fine grained access rights according to SQL-standard

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More resources

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How to Use C# Azure.Data.Tables SDK with Azure Cosmos DB
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How to use Azure Table storage in .Net
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16 May 2023, DevOps.com

How to write data to Azure Table Store with an Azure Function
14 April 2017, Experts Exchange

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