DBMS > DolphinDB vs. GreptimeDB vs. Microsoft Azure Synapse Analytics vs. searchxml

System Properties Comparison DolphinDB vs. GreptimeDB vs. Microsoft Azure Synapse Analytics vs. searchxml

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Editorial information provided by DB-Engines

Name

Description

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

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

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

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Time Series DBMS

Relational DBMS

Native XML DBMS
Search engine

Secondary database models

Relational DBMS

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

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	0.06
Rank	#352	Overall
	#33	Time Series DBMS

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	0.00
Rank	#383	Overall
	#7	Native XML DBMS
	#25	Search engines

Website

www.dolphindb.com

greptime.com

azure.microsoft.com/services/synapse-analytics

www.searchxml.net/category/products

Technical documentation

docs.dolphindb.cn/en/help200/index.html

docs.greptime.com

docs.microsoft.com/azure/synapse-analytics

www.searchxml.net/support/handouts

Developer

DolphinDB, Inc

Greptime Inc.

Microsoft

informationpartners gmbh

Initial release

2018

2022

2016

2015

Current release

v2.00.4, January 2022

1.0

License

Commercial or Open Source

commercial

free community version available

Open Source

Apache Version 2.0

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

C++

Rust

C++

Server operating systems

Linux
Windows

Android
Docker
FreeBSD
Linux
macOS
Windows

hosted

Windows

Data scheme

yes

schema-free, schema definition possible

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

gRPC
HTTP API
JDBC

ADO.NET
JDBC
ODBC

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

C++
Erlang
Go
Java
JavaScript

C#
Java
PHP

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

yes

Python

Transact SQL

yes

on the application server

Triggers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Sharding, horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

sychronisation to multiple collections

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

yes

ACID

multiple readers, single writer

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.

yes

User concepts

Access control

Administrators, Users, Groups

Simple rights management via user accounts

yes

Domain, group and role-based access control at the document level and for application services

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

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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