DBMS > GreptimeDB vs. H2GIS vs. KairosDB vs. Microsoft Azure Data Explorer vs. SpatiaLite

System Properties Comparison GreptimeDB vs. H2GIS vs. KairosDB vs. Microsoft Azure Data Explorer vs. SpatiaLite

Editorial information provided by DB-Engines

Name

Description

An open source Time Series DBMS built for increased scalability, high performance and efficiency

Spatial extension of H2

Distributed Time Series DBMS based on Cassandra or H2

Fully managed big data interactive analytics platform

Spatial extension of SQLite

Primary database model

column oriented

Secondary database models

Relational DBMS

Document store

If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store

this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine

support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS

see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis

Relational DBMS

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

Score	0.06
Rank	#352	Overall
	#33	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Score	4.38
Rank	#77	Overall
	#41	Relational DBMS

Score	1.60
Rank	#149	Overall
	#3	Spatial DBMS

Website

greptime.com

www.h2gis.org

github.com/kairosdb/kairosdb

azure.microsoft.com/services/data-explorer

www.gaia-gis.it/fossil/libspatialite/index

Technical documentation

docs.greptime.com

www.h2gis.org/docs/home

kairosdb.github.io

docs.microsoft.com/en-us/azure/data-explorer

www.gaia-gis.it/gaia-sins/spatialite_topics.html

Developer

Greptime Inc.

CNRS

Microsoft

Alessandro Furieri

Initial release

2022

2013

2019

2008

Current release

1.2.2, November 2018

cloud service with continuous releases

5.0.0, August 2020

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

LGPL 3.0

Open Source

Apache 2.0

commercial

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

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

Rust

Java

C++

Server operating systems

Android
Docker
FreeBSD
Linux
macOS
Windows

Linux
OS X
Windows

hosted

server-less

Data scheme

schema-free, schema definition possible

yes

schema-free

Fixed schema with schema-less datatypes (dynamic)

yes

Typing

predefined data types such as float or date

yes

bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-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.

yes

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

yes

Kusto Query Language (KQL), SQL subset

yes

APIs and other access methods

gRPC
HTTP API
JDBC

Graphite protocol
HTTP REST
Telnet API

Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API

Supported programming languages

C++
Erlang
Go
Java
JavaScript

Java

Java
JavaScript

Node.js
PHP
Python

.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R

Server-side scripts

Stored procedures

Python

yes

based on H2

Yes, possible languages: KQL, Python, R

Triggers

yes

see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

based on Cassandra

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

based on H2

selectable replication factor

based on Cassandra

yes

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

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Spark connector (open source): github.com/Azure/azure-kusto-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

User concepts

Access control

Simple rights management via user accounts

yes

based on H2

simple password-based access control

Azure Active Directory Authentication

More information provided by the system vendor

Specific characteristics

GreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
» more

Competitive advantages

- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
» more

Typical application scenarios

For IoT industries, GreptimeDB can seamless integrate with message queues and other...
» more

Key customers

Greptime's clients span multiple sectors including IoT, connected vehicles, and energy...
» more

Market metrics

GreptimeDB has garnered global recognition by topping GitHub trends following its...
» more

Licensing and pricing models

GreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
» more

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

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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