DBMS > Google BigQuery vs. QuestDB vs. SAP IQ vs. Splice Machine

System Properties Comparison Google BigQuery vs. QuestDB vs. SAP IQ vs. Splice Machine

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

A high performance open source SQL database for time series data

Columnar RDBMS optimized for Big Data analytics

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

Primary database model

column-oriented

Secondary database models

Relational DBMS

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	2.70
Rank	#105	Overall
	#8	Time Series DBMS

Score	2.64
Rank	#108	Overall
	#52	Relational DBMS

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Website

cloud.google.com/bigquery

questdb.io

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

splicemachine.com

Technical documentation

cloud.google.com/bigquery/docs

questdb.io/docs

help.sap.com/docs/SAP_IQ

splicemachine.com/how-it-works

Developer

Google

QuestDB Technology Inc

SAP, formerly Sybase

Splice Machine

Initial release

2010

2014

1994

2014

Current release

16.1 SPS04, April 2019

3.1, March 2021

License

Commercial or Open Source

commercial

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

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

Java

Server operating systems

hosted

Linux
macOS
Windows

AIX
HP-UX
Linux
Solaris
Windows

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free via InfluxDB Line Protocol

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

yes

SQL with time-series extensions

yes

APIs and other access methods

RESTful HTTP/JSON API

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

ADO.NET
JDBC
ODBC
RESTful HTTP API

JDBC
Native Spark Datasource
ODBC

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

over HTTP

C
C#
C++
Java
Perl
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning (by timestamps)

shared disk or shared nothing architectures with SAP IQ Multiplexer

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication with eventual consistency

SAP/Sybase Replication Server

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

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

Since BigQuery is designed for querying 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

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

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

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

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

News

Fluid real-time dashboards with Grafana and QuestDB
11 June 2024

QuestDB 8.0: Major Release
23 May 2024

QuestDB and Raspberry Pi 5 benchmark, a pocket-sized powerhouse
8 May 2024

Build your own resource monitor with QuestDB and Grafana
6 May 2024

Does "vpmovzxbd" Scare You? Here's Why it Doesn't Have To
12 April 2024

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