DBMS > Databricks vs. HugeGraph vs. QuestDB vs. RocksDB vs. STSdb

System Properties Comparison Databricks vs. HugeGraph vs. QuestDB vs. RocksDB vs. STSdb

Editorial information provided by DB-Engines

Name

Description

The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.

A fast-speed and highly-scalable Graph DBMS

A high performance open source SQL database for time series data

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Document store
Relational DBMS

Graph DBMS

Time Series DBMS

Key-value store

Secondary database models

Relational DBMS

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

Score	81.08
Rank	#15	Overall
	#2	Document stores
	#10	Relational DBMS

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	2.70
Rank	#105	Overall
	#8	Time Series DBMS

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

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Website

www.databricks.com

github.com/hugegraph
hugegraph.apache.org

questdb.io

rocksdb.org

github.com/STSSoft/STSdb4

Technical documentation

docs.databricks.com

hugegraph.apache.org/docs

questdb.io/docs

github.com/facebook/rocksdb/wiki

Developer

Databricks

Baidu

QuestDB Technology Inc

Facebook, Inc.

STS Soft SC

Initial release

2013

2018

2014

2013

2011

Current release

0.9

9.2.1, May 2024

4.0.8, September 2015

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

BSD

Open Source

GPLv2, commercial license available

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

Java

Java (Zero-GC), C++, Rust

C++

Server operating systems

hosted

Linux
macOS
Unix

Linux
macOS
Windows

Linux

Windows

Data scheme

Flexible Schema (defined schema, partial schema, schema free)

yes

schema-free via InfluxDB Line Protocol

schema-free

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

also supports composite index and range index

SQL

Support of SQL

with Databricks SQL

SQL with time-series extensions

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

Java API
RESTful HTTP API
TinkerPop Gremlin

HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol

C++ API
Java API

.NET Client API

Supported programming languages

Python
R
Scala

Groovy
Java
Python

PostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust

over HTTP

C
C++
Go
Java
Perl
Python
Ruby

C#
Java

Server-side scripts

Stored procedures

user defined functions and aggregates

asynchronous Gremlin script jobs

Triggers

Partitioning methods

Methods for storing different data on different nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

horizontal partitioning (by timestamps)

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

Source-replica replication with eventual consistency

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

Transaction concepts

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

ACID

ACID for single-table writes

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

through memory mapped files

yes

User concepts

Access control

Users, roles and permissions

More information provided by the system vendor

Specific characteristics

Supported database models : In addition to the Document store and Relational DBMS...
» more

Relational model with native time series support Column-based storage and time partitioned...
» more

Competitive advantages

High ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more

Typical application scenarios

Financial tick data Industrial IoT Application Metrics Monitoring
» more

Key customers

Banks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more

Licensing and pricing models

Open source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more

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