DBMS > DolphinDB vs. RocksDB vs. StarRocks vs. TempoIQ

System Properties Comparison DolphinDB vs. RocksDB vs. StarRocks vs. TempoIQ

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Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

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.

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

An open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics

Forked from Apache Doris

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Primary database model

Time Series DBMS
Vector DBMS

Key-value store

Relational DBMS

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	2.72
Rank	#100	Overall
	#8	Time Series DBMS
	#5	Vector DBMS

Score	2.84
Rank	#97	Overall
	#16	Key-value stores

Score	0.95
Rank	#193	Overall
	#89	Relational DBMS

Website

www.dolphindb.com

rocksdb.org

www.starrocks.io

tempoiq.com (offline)

Technical documentation

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

github.com/facebook/rocksdb/wiki

docs.starrocks.io/en-us/latest/introduction/StarRocks_intro

Developer

DolphinDB, Inc

Facebook, Inc.

The Linux Foundation

since Feb 2023

TempoIQ

Initial release

2018

2013

2020

2012

Current release

v2.00.4, January 2022

9.4.0, June 2024

3.3, June 2024

License

Commercial or Open Source

commercial

free community version available

Open Source

BSD

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++

C++, Java

Server operating systems

Linux
Windows

Linux

Data scheme

yes

schema-free

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

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

C++ API
Java API

JDBC
MySQL protocol

HTTP API

Supported programming languages

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

C
C++
Go
Java
Perl
Python
Ruby

Java

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

horizontal partitioning (by range and hash)

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

Transaction concepts

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

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.

yes

User concepts

Access control

Administrators, Users, Groups

Role based access control and fine grained access rights

simple authentication-based access control

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