DBMS > Apache Druid vs. GigaSpaces vs. QuestDB vs. RocksDB

System Properties Comparison Apache Druid vs. GigaSpaces vs. QuestDB vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

A high performance open source SQL database for time series data

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

Primary database model

Relational DBMS
Time Series DBMS

Document store
Object oriented DBMS

Values are user defined objects

Time Series DBMS

Key-value store

Secondary database models

Graph DBMS
Search engine

Relational DBMS

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

Score	3.29
Rank	#95	Overall
	#49	Relational DBMS
	#7	Time Series DBMS

Score	1.02
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	2.48
Rank	#115	Overall
	#9	Time Series DBMS

Score	4.00
Rank	#84	Overall
	#11	Key-value stores

Website

Technical documentation

druid.apache.org/docs/latest/design

docs.gigaspaces.com/latest/landing.html

questdb.io/docs

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation and contributors

Gigaspaces Technologies

QuestDB Technology Inc

Facebook, Inc.

Initial release

2012

2000

2014

2013

Current release

29.0.1, April 2024

15.5, September 2020

8.11.4, April 2024

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache Version 2; Commercial licenses available

Open Source

Apache 2.0

Open Source

BSD

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

Java

Java, C++, .Net

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

C++

Server operating systems

Linux
OS X
Unix

Linux
macOS
Solaris
Windows

Linux
macOS
Windows

Linux

Data scheme

yes

schema-less columns are supported

schema-free

yes

schema-free via InfluxDB Line Protocol

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.

XML can be used for describing objects metadata

Secondary indexes

yes

SQL

Support of SQL

SQL for querying

SQL-99 for query and DML statements

SQL with time-series extensions

APIs and other access methods

JDBC
RESTful HTTP/JSON API

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

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

C++ API
Java API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
C++
Java
Python
Scala

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

over HTTP

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes, event driven architecture

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

horizontal partitioning (by timestamps)

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

Source-replica replication with eventual consistency

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

Foreign keys

Referential integrity

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Role-based access control

More information provided by the system vendor

Specific characteristics

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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