DBMS > Graph Engine vs. Kdb vs. QuestDB vs. Snowflake vs. Splice Machine

System Properties Comparison Graph Engine vs. Kdb vs. QuestDB vs. Snowflake vs. Splice Machine

Editorial information provided by DB-Engines

Name

Description

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

High performance Time Series DBMS

A high performance open source SQL database for time series data

Cloud-based data warehousing service for structured and semi-structured data

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Graph DBMS
Key-value store

Time Series DBMS
Vector DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	0.59
Rank	#235	Overall
	#21	Graph DBMS
	#33	Key-value stores

Score	7.06
Rank	#48	Overall
	#2	Time Series DBMS
	#2	Vector DBMS

Score	2.91
Rank	#92	Overall
	#6	Time Series DBMS

Score	142.50
Rank	#7	Overall
	#5	Relational DBMS

Score	0.54
Rank	#242	Overall
	#113	Relational DBMS

Website

Technical documentation

www.graphengine.io/docs/manual

code.kx.com

questdb.io/docs

docs.snowflake.net/manuals/index.html

splicemachine.com/how-it-works

Developer

Microsoft

Kx Systems, a division of First Derivatives plc

QuestDB Technology Inc

Snowflake Computing Inc.

Splice Machine

Initial release

2010

2000

kdb was released 2000, kdb+ in 2003

2014

Current release

3.6, May 2018

3.1, March 2021

License

Commercial or Open Source

Open Source

MIT License

commercial

free 32-bit version

Open Source

Apache 2.0

commercial

Open Source

AGPL 3.0, 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

.NET and C

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

Java

Server operating systems

.NET

Linux
OS X
Solaris
Windows

Linux
macOS
Windows

hosted

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free via InfluxDB Line Protocol

yes

support of semi-structured data formats (JSON, XML, Avro)

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.

yes

Secondary indexes

yes

table attribute 'grouped'

yes

SQL

Support of SQL

SQL-like query language (q)

SQL with time-series extensions

yes

APIs and other access methods

RESTful HTTP API

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

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

CLI Client
JDBC
ODBC

JDBC
Native Spark Datasource
ODBC

Supported programming languages

C#
C++
F#
Visual Basic

C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala

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

over HTTP

JavaScript (Node.js)
Python

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

yes

user defined functions

yes

Java

Triggers

yes

with views

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

horizontal partitioning (by timestamps)

yes

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Source-replica replication with eventual consistency

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

similar paradigm used for internal processing

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID for single-table writes

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

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

through memory mapped files

yes

User concepts

Access control

rights management via user accounts

Users with fine-grained authorization concept, user roles and pluggable authentication

Access rights for users, groups and roles according to SQL-standard

More information provided by the system vendor

Specific characteristics

Integrated columnar database & programming system for streaming, real time and historical...
» more

Competitive advantages

provides seamless scalability; runs on industry standard server platforms; is top-ranked...
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Typical application scenarios

tick database streaming sensor data massive intelligence applications oil and gas...
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Key customers

Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more

Market metrics

kdb+ performance and reliability proven by our customers in critical infrastructure...
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Licensing and pricing models

upon request
» more

News

Time-series and analytical databases walk into a bar
28 October 2024

Monitoring QuestDB with simple curl commands
24 October 2024

QuestDB and Raspberry Pi 5 benchmark, a pocket-sized powerhouse
22 October 2024

The future of fast databases: Lessons from a decade of QuestDB
10 October 2024

QuestDB 8.1.2 - Tabs & Balance
8 October 2024

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