DBMS > GeoMesa vs. HarperDB vs. Microsoft Azure Synapse Analytics vs. Valentina Server

System Properties Comparison GeoMesa vs. HarperDB vs. Microsoft Azure Synapse Analytics vs. Valentina Server

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Editorial information provided by DB-Engines

Name

Description

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

HarperDB takes the "stack" out of "tech stack" by combining an ultra-fast document-style data store, in-memory cache, real-time message broker, and your application components into a single distributed technology.

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

Object-relational database and reports server

Primary database model

Spatial DBMS

Document store

Relational DBMS

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

Score	0.78
Rank	#214	Overall
	#4	Spatial DBMS

Score	0.55
Rank	#243	Overall
	#38	Document stores

Score	18.98
Rank	#31	Overall
	#19	Relational DBMS

Score	0.18
Rank	#313	Overall
	#140	Relational DBMS

Website

www.geomesa.org

www.harperdb.io

azure.microsoft.com/services/synapse-analytics

www.valentina-db.net

Technical documentation

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

docs.harperdb.io/docs

docs.microsoft.com/azure/synapse-analytics

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

CCRi and others

HarperDB

Microsoft

Paradigma Software

Initial release

2014

2017

2016

1999

Current release

5.0.1, July 2024

3.1, August 2021

5.7.5

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

free community edition available

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

Scala

Node.js

C++

Server operating systems

Linux
OS X

hosted

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

APIs and other access methods

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

ADO.NET
JDBC
ODBC

ODBC

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

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

Custom Functions

since release 3.1

Transact SQL

yes

Triggers

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

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

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

yes

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

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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