DBMS > Bangdb vs. GridGain vs. IBM Db2 Event Store vs. SAP IQ vs. XTDB

System Properties Comparison Bangdb vs. GridGain vs. IBM Db2 Event Store vs. SAP IQ vs. XTDB

Editorial information provided by DB-Engines

Name

Description

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

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

Distributed Event Store optimized for Internet of Things use cases

Columnar RDBMS optimized for Big Data analytics

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Document store
Graph DBMS
Time Series DBMS

Key-value store
Relational DBMS

Event Store
Time Series DBMS

Relational DBMS

column-oriented

Document store

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

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

Score	2.75
Rank	#104	Overall
	#53	Relational DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

bangdb.com

www.gridgain.com

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

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

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

docs.bangdb.com

www.gridgain.com/docs/index.html

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

help.sap.com/docs/SAP_IQ

www.xtdb.com/docs

Developer

Sachin Sinha, BangDB

GridGain Systems, Inc.

IBM

SAP, formerly Sybase

Juxt Ltd.

Initial release

2012

2007

2017

1994

2019

Current release

BangDB 2.0, October 2021

GridGain 8.5.1

2.0

16.1 SPS04, April 2019

1.19, September 2021

License

Commercial or Open Source

Open Source

BSD 3

commercial

free developer edition available

commercial

Open Source

MIT License

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++

Java, C++, .Net

C and C++

Clojure

Server operating systems

Linux

Linux
OS X
Solaris
Windows

Linux

Linux, macOS, Windows for the developer addition

AIX
HP-UX
Linux
Solaris
Windows

All OS with a Java 8 (and higher) VM
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, extensible-data-notation format

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

yes

through the embedded Spark runtime

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

Proprietary protocol
RESTful HTTP API

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

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
RESTful HTTP API

HTTP REST
JDBC

Supported programming languages

C
C#
C++
Java
Python

C#
C++
Java
PHP
Python
Ruby
Scala

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

C
C#
C++
Java
Perl
PHP
Python
Ruby

Clojure
Java

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

Sharding

shared disk or shared nothing architectures with SAP IQ Multiplexer

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes (replicated cache)

Active-active shard replication

SAP/Sybase Replication Server

yes, each node contains all data

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

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

No - written data is immutable

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

fine grained access rights according to SQL-standard

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