DBMS > EJDB vs. Google BigQuery vs. IBM Db2 Event Store vs. RRDtool

System Properties Comparison EJDB vs. Google BigQuery vs. IBM Db2 Event Store vs. RRDtool

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Editorial information provided by DB-Engines

Name

Description

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Large scale data warehouse service with append-only tables

Distributed Event Store optimized for Internet of Things use cases

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

Primary database model

Document store

Relational DBMS

Event Store
Time Series DBMS

Time Series DBMS

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

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Website

github.com/Softmotions/ejdb

cloud.google.com/bigquery

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

oss.oetiker.ch/rrdtool

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

cloud.google.com/bigquery/docs

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

oss.oetiker.ch/rrdtool/doc

Developer

Softmotions

Google

IBM

Tobias Oetiker

Initial release

2012

2010

2017

1999

Current release

2.0

1.8.0, 2022

License

Commercial or Open Source

Open Source

GPLv2

commercial

free developer edition available

Open Source

GPL V2 and FLOSS

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++

Implementations in Java (e.g. RRD4J) and C# available

Server operating systems

server-less

hosted

Linux

Linux, macOS, Windows for the developer addition

HP-UX
Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

Numeric data only

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.

Exporting into and restoring from XML files possible

Secondary indexes

SQL

Support of SQL

yes

through the embedded Spark runtime

APIs and other access methods

in-process shared library

RESTful HTTP/JSON API

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

in-process shared library
Pipes

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

.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

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Active-active shard replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

none

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

Transaction concepts

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

Since BigQuery is designed for querying data

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

No - written data is immutable

yes

by using the rrdcached daemon

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

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