DBMS > Firebird vs. Memcached vs. Microsoft Azure Cosmos DB vs. Splice Machine vs. Splunk

System Properties Comparison Firebird vs. Memcached vs. Microsoft Azure Cosmos DB vs. Splice Machine vs. Splunk

Editorial information provided by DB-Engines

Name

Description

Firebird is an open source RDBMS forked from Borland's InterBase

In-memory key-value store, originally intended for caching

Globally distributed, horizontally scalable, multi-model database service

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Analytics Platform for Big Data

Primary database model

Relational DBMS

Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Search engine

Secondary database models

Spatial DBMS

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

Score	20.82
Rank	#30	Overall
	#18	Relational DBMS

Score	19.42
Rank	#32	Overall
	#4	Key-value stores

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Score	86.45
Rank	#14	Overall
	#2	Search engines

Website

www.firebirdsql.org

www.memcached.org

azure.microsoft.com/services/cosmos-db

splicemachine.com

www.splunk.com

Technical documentation

www.firebirdsql.org/en/reference-manuals

github.com/memcached/memcached/wiki

learn.microsoft.com/azure/cosmos-db

splicemachine.com/how-it-works

docs.splunk.com/Documentation/Splunk

Developer

Firebird Foundation

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Microsoft

Splice Machine

Splunk Inc.

Initial release

2000

As fork of Borland's InterBase

2003

2014

2003

Current release

5.0.0, January 2024

1.6.27, May 2024

3.1, March 2021

License

Commercial or Open Source

Open Source

Initial Developer's Public License

Open Source

BSD license

commercial

Open Source

AGPL 3.0, commercial license available

commercial

Limited free edition and free developer edition available

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 and C++

Java

Server operating systems

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

FreeBSD
Linux
OS X
Unix
Windows

hosted

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON 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.

yes

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

yes

SQL-like query language

yes

Splunk Search Processing Language for search commands

APIs and other access methods

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

Proprietary protocol

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

JDBC
Native Spark Datasource
ODBC

HTTP REST

Supported programming languages

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

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

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

PSQL

JavaScript

yes

Java

yes

Triggers

yes

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Shared Nothhing Auto-Sharding, Columnar Partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Repcached, a Memcached patch, provides this functionallity

yes

Implicit feature of the cloud service

Multi-source replication
Source-replica replication

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Yes, via Full Spark Integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

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

Features a multi-generational MVCC architecture, readers do not block writers

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

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

Users with fine-grained authorization concept

yes

using SASL (Simple Authentication and Security Layer) protocol

Access rights can be defined down to the item level

Access rights for users, groups and roles according to SQL-standard

Access rights for users and roles

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