DBMS > BigObject vs. IBM Db2 Event Store vs. InfinityDB vs. ToroDB

System Properties Comparison BigObject vs. IBM Db2 Event Store vs. InfinityDB vs. ToroDB

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Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Analytic DBMS for real-time computations and queries

Distributed Event Store optimized for Internet of Things use cases

A Java embedded Key-Value Store which extends the Java Map interface

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Event Store
Time Series DBMS

Key-value store

Document store

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

Score	0.13
Rank	#329	Overall
	#147	Relational DBMS

Score	0.18
Rank	#315	Overall
	#2	Event Stores
	#26	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#59	Key-value stores

Website

bigobject.io

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

boilerbay.com

github.com/torodb/server

Technical documentation

docs.bigobject.io

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

boilerbay.com/infinitydb/manual

Developer

BigObject, Inc.

IBM

Boiler Bay Inc.

8Kdata

Initial release

2015

2017

2002

2016

Current release

2.0

4.0

License

Commercial or Open Source

commercial

free community edition available

commercial

free developer edition available

commercial

Open Source

AGPL-V3

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C and C++

Java

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux

Linux, macOS, Windows for the developer addition

All OS with a Java VM

All OS with a Java 7 VM

Data scheme

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

schema-free

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

yes

string, integer, double, boolean, date, object_id

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

manual creation possible, using inversions based on multi-value capability

SQL

Support of SQL

SQL-like DML and DDL statements

yes

through the embedded Spark runtime

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

Supported programming languages

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

Java

Server-side scripts

Stored procedures

Lua

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Active-active shard replication

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Immediate Consistency

READ-COMMITTED or SERIALIZED

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

manual creation possible, using inversions based on multi-value capability

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

fine grained access rights according to SQL-standard

Access rights for users and roles

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