DBMS > Databend vs. GeoMesa vs. LMDB vs. SiriDB vs. Snowflake

System Properties Comparison Databend vs. GeoMesa vs. LMDB vs. SiriDB vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

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

A high performant, light-weight, embedded key-value database library

Open Source Time Series DBMS

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

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

Score	0.34
Rank	#283	Overall
	#130	Relational DBMS

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	2.09
Rank	#121	Overall
	#20	Key-value stores

Score	0.07
Rank	#378	Overall
	#42	Time Series DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

github.com/datafuselabs/databend
www.databend.com

www.geomesa.org

www.symas.com/symas-embedded-database-lmdb

siridb.com

www.snowflake.com

Technical documentation

docs.databend.com

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

www.lmdb.tech/doc

docs.siridb.com

docs.snowflake.net/manuals/index.html

Developer

Databend Labs

CCRi and others

Symas

Cesbit

Snowflake Computing Inc.

Initial release

2021

2014

2011

2017

2014

Current release

1.0.59, April 2023

5.0.0, May 2024

0.9.32, January 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache License 2.0

Open Source

MIT License

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

Rust

Scala

Server operating systems

hosted
Linux
macOS

Linux
Unix
Windows

Linux

hosted

Data scheme

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

Numeric data

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

APIs and other access methods

CLI Client
JDBC
RESTful HTTP API

HTTP API

CLI Client
JDBC
ODBC

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

depending on storage layer

none

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

depending on storage layer

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on storage layer

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

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.

depending on storage layer

yes

User concepts

Access control

Users with fine-grained authorization concept, user roles

yes

depending on the DBMS used for storage

simple rights management via user accounts

Users with fine-grained authorization concept, user roles and pluggable authentication

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