DBMS > GeoMesa vs. HarperDB vs. Microsoft Azure Synapse Analytics vs. TDengine vs. WakandaDB

System Properties Comparison GeoMesa vs. HarperDB vs. Microsoft Azure Synapse Analytics vs. TDengine vs. WakandaDB

Editorial information provided by DB-Engines

Name

Description

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

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

Time Series DBMS and big data platform

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Secondary database models

Relational DBMS

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

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	2.60
Rank	#107	Overall
	#8	Time Series DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

www.geomesa.org

www.harperdb.io

azure.microsoft.com/services/synapse-analytics

github.com/taosdata/TDengine
tdengine.com

wakanda.github.io

Technical documentation

www.geomesa.org/documentation/stable/user/index.html

docs.harperdb.io/docs

docs.microsoft.com/azure/synapse-analytics

docs.tdengine.com

wakanda.github.io/doc

Developer

CCRi and others

HarperDB

Microsoft

TDEngine, previously Taos Data

Wakanda SAS

Initial release

2014

2017

2016

2019

2012

Current release

5.0.0, May 2024

3.1, August 2021

3.0, August 2022

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

free community edition available

commercial

Open Source

AGPL V3, also commercial editions available

Open Source

AGPLv3, extended commercial license 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

Scala

Node.js

C++

C++, JavaScript

Server operating systems

Linux
OS X

hosted

Linux
Windows

Linux
OS X
Windows

Data scheme

yes

dynamic schema

yes

Typing

predefined data types such as float or date

yes

JSON data types

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

yes

SQL

Support of SQL

SQL-like data manipulation statements

yes

Standard SQL with extensions for time-series applications

APIs and other access methods

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

ADO.NET
JDBC
ODBC

JDBC
RESTful HTTP API

RESTful HTTP API

Supported programming languages

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

C#
Java
PHP

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

JavaScript

Server-side scripts

Stored procedures

Custom Functions

since release 3.1

Transact SQL

yes

Triggers

yes, via alarm monitoring

yes

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

A table resides as a whole on one (or more) nodes in a cluster

Sharding, horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

yes

the nodes on which a table resides can be defined

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

depending on storage layer

Immediate Consistency

Foreign keys

Referential integrity

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

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using LMDB

yes

In-memory capabilities

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

depending on storage layer

yes

User concepts

Access control

yes

depending on the DBMS used for storage

Access rights for users and roles

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...
» more

Market metrics

TDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more

Licensing and pricing models

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

News

Seamless Data Integration from MQTT and InfluxDB to TDengine
22 May 2024

Solving Long Query Performance Bottlenecks
22 May 2024

What Is Predictive Maintenance?
17 May 2024

Can Typical Time-Series Databases Replace Data Historians?
8 May 2024

TDengine 3.3.0.0 Release Notes
7 May 2024

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

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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