DBMS > Apache Doris vs. GeoMesa vs. Microsoft Azure Synapse Analytics vs. RocksDB vs. Warp 10

System Properties Comparison Apache Doris vs. GeoMesa vs. Microsoft Azure Synapse Analytics vs. RocksDB vs. Warp 10

Editorial information provided by DB-Engines

Name

Description

An MPP-based analytics DBMS embracing the MySQL protocol

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

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

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

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

Score	0.60
Rank	#247	Overall
	#113	Relational DBMS

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	0.14
Rank	#344	Overall
	#32	Time Series DBMS

Website

doris.apache.org
github.com/apache/doris

www.geomesa.org

azure.microsoft.com/services/synapse-analytics

rocksdb.org

www.warp10.io

Technical documentation

github.com/apache/doris/wiki

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

docs.microsoft.com/azure/synapse-analytics

github.com/facebook/rocksdb/wiki

www.warp10.io/content/02_Getting_started

Developer

Apache Software Foundation, originally contributed from Baidu

CCRi and others

Microsoft

Facebook, Inc.

SenX

Initial release

2017

2014

2016

2013

2015

Current release

1.2.2, February 2023

5.0.0, May 2024

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache License 2.0

commercial

Open Source

BSD

Open Source

Apache License 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Scala

C++

Java

Server operating systems

Linux

hosted

Linux

Linux
OS X
Windows

Data scheme

yes

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

JDBC
MySQL client

ADO.NET
JDBC
ODBC

C++ API
Java API

HTTP API
Jupyter
WebSocket

Supported programming languages

Java

C#
Java
PHP

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

Transact SQL

yes

WarpScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

depending on storage layer

Sharding, horizontal partitioning

horizontal partitioning

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

none

depending on storage layer

yes

selectable replication factor

based on HBase

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

based on HBase

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

ACID

yes

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

fine grained access rights according to SQL-standard

yes

depending on the DBMS used for storage

yes

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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