DBMS > Datomic vs. GBase vs. Microsoft Azure Synapse Analytics vs. NSDb vs. Ultipa

System Properties Comparison Datomic vs. GBase vs. Microsoft Azure Synapse Analytics vs. NSDb vs. Ultipa

Editorial information provided by DB-Engines

Name

Description

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

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

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

High performance Graph DBMS supporting HTAP high availability cluster deployment

Primary database model

Relational DBMS

Time Series DBMS

Graph DBMS

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

Score	1.55
Rank	#144	Overall
	#67	Relational DBMS

Score	1.11
Rank	#173	Overall
	#78	Relational DBMS

Score	18.98
Rank	#31	Overall
	#19	Relational DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	0.11
Rank	#338	Overall
	#32	Graph DBMS

Website

www.datomic.com

www.gbase.cn

azure.microsoft.com/services/synapse-analytics

nsdb.io

www.ultipa.com

Technical documentation

docs.datomic.com

docs.microsoft.com/azure/synapse-analytics

nsdb.io/Architecture

www.ultipa.com/document

Developer

Cognitect

General Data Technology Co., Ltd.

Microsoft

Ultipa

Initial release

2012

2004

2016

2017

2019

Current release

1.0.7180, July 2024

GBase 8a, GBase 8s, GBase 8c

License

Commercial or Open Source

commercial

limited edition free

commercial

Open Source

Apache Version 2.0

commercial

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

Java, Clojure

C, Java, Python

C++

Java, Scala

Server operating systems

All OS with a Java VM

Linux

hosted

Linux
macOS

Data scheme

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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

Secondary indexes

yes

all fields are automatically indexed

SQL

Support of SQL

Standard with numerous extensions

yes

SQL-like query language

APIs and other access methods

RESTful HTTP API

ADO.NET
C API
JDBC
ODBC

ADO.NET
JDBC
ODBC

gRPC
HTTP REST
WebSocket

RESTful HTTP API

Supported programming languages

Clojure
Java

C#
Java
PHP

Java
Scala

C++
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Transaction Functions

user defined functions

Transact SQL

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

Using Apache Lucene

In-memory capabilities

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

yes

recommended only for testing and development

User concepts

Access control

yes

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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Nubank released the licenses of its Datomic database
21 May 2023, Desde Linux

Lucas Cavalcanti on Using Clojure, Microservices, Hexagonal Architecture and Public Cloud at Nubank
16 August 2021, InfoQ.com

Nubank acquires US company; PayPal studies cryptocurrencies
24 July 2020, iupana.com

Zoona Case Study
16 December 2017, AWS Blog

Brazilian challenger Nubank acquires firm behind Clojure and Datomic
28 July 2020, FinTech Futures

provided by Google News

General Available: Azure Synapse Runtime for Apache Spark 3.4 is now GA
8 April 2024, Microsoft

Azure Synapse Runtime for Apache Spark 3.2 End of Support
22 March 2024, Microsoft

Azure Synapse vs. Databricks: Data Platform Comparison 2024
26 March 2024, eWeek

Announcing General Availability of Graph Semantics in Kusto
27 May 2024, Microsoft

Migrate Microsoft Azure Synapse Analytics to Amazon Redshift using AWS SCT
18 October 2023, AWS Blog

provided by Google News

Ultipa, Inc. Announces Key Updates to Its Global Partnership Program
21 August 2024, EIN News

provided by Google News

Share this page