DBMS > Datomic vs. Google BigQuery vs. Microsoft Azure Synapse Analytics vs. SAP SQL Anywhere vs. TDengine

System Properties Comparison Datomic vs. Google BigQuery vs. Microsoft Azure Synapse Analytics vs. SAP SQL Anywhere vs. TDengine

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

Large scale data warehouse service with append-only tables

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

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Time Series DBMS and big data platform

Primary database model

Relational DBMS

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Score	2.60
Rank	#107	Overall
	#8	Time Series DBMS

Website

www.datomic.com

cloud.google.com/bigquery

azure.microsoft.com/services/synapse-analytics

www.sap.com/products/technology-platform/sql-anywhere.html

github.com/taosdata/TDengine
tdengine.com

Technical documentation

docs.datomic.com

cloud.google.com/bigquery/docs

docs.microsoft.com/azure/synapse-analytics

help.sap.com/docs/SAP_SQL_Anywhere

docs.tdengine.com

Developer

Cognitect

Google

Microsoft

SAP

formerly Sybase

TDEngine, previously Taos Data

Initial release

2012

2010

2016

1992

2019

Current release

1.0.6735, June 2023

17, July 2015

3.0, August 2022

License

Commercial or Open Source

commercial

limited edition free

commercial

Open Source

AGPL V3, also commercial editions available

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++

Server operating systems

All OS with a Java VM

hosted

AIX
HP-UX
Linux
OS X
Solaris
Windows

Linux
Windows

Data scheme

yes

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

Standard SQL with extensions for time-series applications

APIs and other access methods

RESTful HTTP API

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

ADO.NET
HTTP API
JDBC
ODBC

JDBC
RESTful HTTP API

Supported programming languages

Clojure
Java

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
Java
PHP

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

C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust

Server-side scripts

Stored procedures

yes

Transaction Functions

user defined functions

in JavaScript

Transact SQL

yes, in C/C++, Java, .Net or Perl

Triggers

By using transaction functions

yes

yes, via alarm monitoring

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

none

Sharding, horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

yes

Source-replica replication

Database mirroring

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

yes

Transaction concepts

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

ACID

Since BigQuery is designed for querying 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

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

yes

User concepts

Access control

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

Google Cloud Identity & Access Management (IAM)

yes

fine grained access rights according to SQL-standard

yes

More information provided by the system vendor

Specific characteristics

TDengine™ is a next generation data historian purpose-built for Industry 4.0 and...
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Competitive advantages

High Performance at any Scale: TDengine is purpose-built for handling massive industrial...
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Typical application scenarios

TDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
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Market metrics

TDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
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Licensing and pricing models

TDengine OSS is an open source, cloud native time series database. It includes built-in...
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News

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17 May 2024

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8 May 2024

TDengine 3.3.0.0 Release Notes
7 May 2024

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6 May 2024

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