DBMS > Bangdb vs. FatDB vs. Lovefield vs. SQream DB vs. TempoIQ

System Properties Comparison Bangdb vs. FatDB vs. Lovefield vs. SQream DB vs. TempoIQ

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

Description

Converged and high performance database for device data, events, time series, document and graph

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Embeddable relational database for web apps written in pure JavaScript

a GPU-based, columnar RDBMS for big data analytics workloads

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Primary database model

Document store
Graph DBMS
Time Series DBMS

Document store
Key-value store

Relational DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	0.70
Rank	#227	Overall
	#104	Relational DBMS

Website

bangdb.com

google.github.io/lovefield

sqream.com

tempoiq.com (offline)

Technical documentation

docs.bangdb.com

github.com/google/lovefield/blob/master/docs/spec_index.md

docs.sqream.com

Developer

Sachin Sinha, BangDB

FatCloud

Google

SQream Technologies

TempoIQ

Initial release

2012

2014

2017

2012

Current release

BangDB 2.0, October 2021

2.1.12, February 2017

2022.1.6, December 2022

License

Commercial or Open Source

Open Source

BSD 3

commercial

Open Source

Apache 2.0

commercial

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, C++

JavaScript

C++, CUDA, Haskell, Java, Scala

Server operating systems

Linux

Windows

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

yes

yes, ANSI Standard SQL Types

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

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

Via inetgration in SQL Server

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

.Net
JDBC
ODBC

HTTP API

Supported programming languages

C
C#
C++
Java
Python

JavaScript

C++
Java
JavaScript (Node.js)
Python

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

yes

via applications

user defined functions in Python

Triggers

yes, Notifications (with Streaming only)

yes

via applications

Using read-only observers

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Sharding

none

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes, run db with in-memory only mode

yes

using MemoryDB

User concepts

Access control

yes (enterprise version only)

Can implement custom security layer via applications

simple authentication-based access control

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