DBMS > IBM Db2 Event Store vs. InfluxDB vs. SpaceTime

System Properties Comparison IBM Db2 Event Store vs. InfluxDB vs. SpaceTime

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Editorial information provided by DB-Engines

Name

Description

Distributed Event Store optimized for Internet of Things use cases

DBMS for storing time series, events and metrics

SpaceTime is a spatio-temporal DBMS with a focus on performance.

Primary database model

Event Store
Time Series DBMS

Time Series DBMS

Spatial DBMS

Secondary database models

Spatial DBMS

with GEO package

Relational DBMS

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

Score	0.18
Rank	#312	Overall
	#2	Event Stores
	#26	Time Series DBMS

Score	21.54
Rank	#28	Overall
	#1	Time Series DBMS

Score	0.00
Rank	#382	Overall
	#7	Spatial DBMS

Website

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

www.influxdata.com/products/influxdb-overview

www.mireo.com/spacetime

Technical documentation

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

docs.influxdata.com/influxdb

Developer

IBM

Mireo

Initial release

2017

2013

2020

Current release

2.0

2.7.6, April 2024

License

Commercial or Open Source

commercial

free developer edition available

Open Source

MIT-License; commercial enterprise version available

commercial

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

C and C++

C++

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

Linux
OS X

through Homebrew

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data and Strings

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

SQL

Support of SQL

yes

through the embedded Spark runtime

SQL-like query language

A subset of ANSI SQL is implemented

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

HTTP API
JSON over UDP

RESTful HTTP API

Supported programming languages

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

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

C#
C++
Python

Server-side scripts

Stored procedures

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

in enterprise version only

Fixed-grid hypercubes

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

selectable replication factor

in enterprise version only

Real-time block device replication (DRBD)

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Concurrency

Support for concurrent manipulation of data

No - written data is immutable

yes

Durability

Support for making data persistent

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

Depending on used storage engine

User concepts

Access control

fine grained access rights according to SQL-standard

simple rights management via user accounts

yes

More information provided by the system vendor

News

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17 April 2025

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15 April 2025

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9 April 2025

Optimizing SQL (and DataFrames) in DataFusion: Part 2
3 April 2025

Simplifying Multi-Node Setups with InfluxDB 3 Enterprise Modes
2 April 2025

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More resources

DB-Engines blog posts

Why Build a Time Series Data Platform?
20 July 2017, Paul Dix (guest author)

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

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provided by Google News

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