DBMS > BigObject vs. Graph Engine vs. StarRocks

System Properties Comparison BigObject vs. Graph Engine vs. StarRocks

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

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

Forked from Apache Doris

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Graph DBMS
Key-value store

Relational DBMS

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

Score	0.14
Rank	#328	Overall
	#148	Relational DBMS

Score	0.54
Rank	#240	Overall
	#21	Graph DBMS
	#33	Key-value stores

Score	1.13
Rank	#170	Overall
	#78	Relational DBMS

Website

bigobject.io

www.graphengine.io

www.starrocks.io

Technical documentation

docs.bigobject.io

www.graphengine.io/docs/manual

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

Developer

BigObject, Inc.

Microsoft

The Linux Foundation

since Feb 2023

Initial release

2015

2010

2020

Current release

3.3, June 2024

License

Commercial or Open Source

commercial

free community edition available

Open Source

MIT License

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

.NET and C

C++, Java

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

.NET

Linux

Data scheme

yes

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 DML and DDL statements

yes

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

RESTful HTTP API

JDBC
MySQL protocol

Supported programming languages

C#
C++
F#
Visual Basic

Java

Server-side scripts

Stored procedures

Lua

yes

user defined functions

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

horizontal partitioning (by range and hash)

Replication methods

Methods for redundantly storing data on multiple nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

Transaction concepts

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

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

Role based access control and fine grained access rights

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