DBMS > Bangdb vs. Drizzle vs. EsgynDB vs. H2 vs. Splunk

System Properties Comparison Bangdb vs. Drizzle vs. EsgynDB vs. H2 vs. Splunk

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

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

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Analytics Platform for Big Data

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Search engine

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	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	86.45
Rank	#14	Overall
	#2	Search engines

Website

Technical documentation

docs.bangdb.com

www.h2database.com/html/main.html

docs.splunk.com/Documentation/Splunk

Developer

Sachin Sinha, BangDB

Drizzle project, originally started by Brian Aker

Esgyn

Thomas Mueller

Splunk Inc.

Initial release

2012

2008

2015

2005

2003

Current release

BangDB 2.0, October 2021

7.2.4, September 2012

2.2.220, July 2023

License

Commercial or Open Source

Open Source

BSD 3

Open Source

GNU GPL

commercial

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

Limited free edition and free developer edition available

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++

C++, Java

Java

Server operating systems

Linux

FreeBSD
Linux
OS X

Linux

All OS with a Java VM

Linux
OS X
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

yes

with proprietary extensions

yes

Splunk Search Processing Language for search commands

APIs and other access methods

Proprietary protocol
RESTful HTTP API

JDBC

ADO.NET
JDBC
ODBC

JDBC
ODBC

HTTP REST

Supported programming languages

C
C#
C++
Java
Python

C
C++
Java
PHP

All languages supporting JDBC/ODBC/ADO.Net

Java

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

Java Stored Procedures

Java Stored Procedures and User-Defined Functions

yes

Triggers

yes, Notifications (with Streaming only)

hooks for callbacks inside the server can be used.

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

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication
Source-replica replication

Multi-source replication between multi datacenters

With clustering: 2 database servers on different computers operate on identical copies of a database

Multi-source replication

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

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

yes, multi-version concurrency control (MVCC)

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)

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

Access rights for users and roles

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