DBMS > Bangdb vs. Cachelot.io vs. GridGain vs. JaguarDB vs. SAP IQ

System Properties Comparison Bangdb vs. Cachelot.io vs. GridGain vs. JaguarDB vs. SAP IQ

Editorial information provided by DB-Engines

Name

Description

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

In-memory caching system

GridGain is an in-memory computing platform, built on Apache Ignite

Performant, highly scalable DBMS for AI and IoT applications

Columnar RDBMS optimized for Big Data analytics

Primary database model

Document store
Graph DBMS
Time Series DBMS

Key-value store

Key-value store
Relational DBMS

Key-value store
Vector DBMS

Relational DBMS

column-oriented

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	0.00
Rank	#383	Overall
	#60	Key-value stores

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	2.75
Rank	#104	Overall
	#53	Relational DBMS

Website

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

Technical documentation

docs.bangdb.com

www.gridgain.com/docs/index.html

www.jaguardb.com/support.html

help.sap.com/docs/SAP_IQ

Developer

Sachin Sinha, BangDB

GridGain Systems, Inc.

DataJaguar, Inc.

SAP, formerly Sybase

Initial release

2012

2015

2007

2015

1994

Current release

BangDB 2.0, October 2021

GridGain 8.5.1

3.3 July 2023

16.1 SPS04, April 2019

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Simplified BSD License

commercial

Open Source

GPL V3.0

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, C++

C++

Java, C++, .Net

C++

the server part. Clients available in other languages

Server operating systems

Linux

FreeBSD
Linux
OS X

Linux
OS X
Solaris
Windows

Linux

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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

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.

yes

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

ANSI-99 for query and DML statements, subset of DDL

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

Memcached protocol

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

JDBC
ODBC

ADO.NET
JDBC
ODBC
RESTful HTTP API

Supported programming languages

C
C#
C++
Java
Python

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

C#
C++
Java
PHP
Python
Ruby
Scala

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

C
C#
C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

yes

Triggers

yes, Notifications (with Streaming only)

yes (cache interceptors and events)

yes

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

none

Sharding

shared disk or shared nothing architectures with SAP IQ Multiplexer

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

yes (replicated cache)

Multi-source replication

SAP/Sybase Replication Server

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

none

Immediate Consistency

Eventual 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

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

User concepts

Access control

yes (enterprise version only)

Security Hooks for custom implementations

rights management via user accounts

fine grained access rights according to SQL-standard

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