DBMS > Google BigQuery vs. IBM Db2 Event Store vs. Microsoft Azure Synapse Analytics vs. Warp 10

System Properties Comparison Google BigQuery vs. IBM Db2 Event Store vs. Microsoft Azure Synapse Analytics vs. Warp 10

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

Distributed Event Store optimized for Internet of Things use cases

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Relational DBMS

Event Store
Time Series DBMS

Relational DBMS

Time Series DBMS

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.27
Rank	#309	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	0.14
Rank	#344	Overall
	#32	Time Series DBMS

Website

cloud.google.com/bigquery

www.ibm.com/products/db2-event-store

azure.microsoft.com/services/synapse-analytics

www.warp10.io

Technical documentation

cloud.google.com/bigquery/docs

www.ibm.com/docs/en/db2-event-store

docs.microsoft.com/azure/synapse-analytics

www.warp10.io/content/02_Getting_started

Developer

Google

IBM

Microsoft

SenX

Initial release

2010

2017

2016

2015

Current release

2.0

License

Commercial or Open Source

commercial

free developer edition available

commercial

Open Source

Apache License 2.0

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

C and C++

C++

Java

Server operating systems

hosted

Linux

Linux, macOS, Windows for the developer addition

hosted

Linux
OS X
Windows

Data scheme

yes

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.

Secondary indexes

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

yes

APIs and other access methods

RESTful HTTP/JSON API

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

HTTP API
Jupyter
WebSocket

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

C#
Java
PHP

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Transact SQL

yes

WarpScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Sharding, horizontal partitioning

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

yes

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared 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

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

yes

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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