DBMS > Atos Standard Common Repository vs. Blueflood vs. CrateDB vs. Splunk vs. Yaacomo

System Properties Comparison Atos Standard Common Repository vs. Blueflood vs. CrateDB vs. Splunk vs. Yaacomo

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

Scalable TimeSeries DBMS based on Cassandra

Distributed Database based on Lucene

Analytics Platform for Big Data

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Document store
Key-value store

Time Series DBMS

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Search engine

Relational DBMS

Secondary database models

Relational DBMS

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

Score	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Score	0.71
Rank	#227	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#10	Vector DBMS

Score	89.10
Rank	#14	Overall
	#2	Search engines

Website

atos.net/en/convergence-creators/portfolio/standard-common-repository

blueflood.io

cratedb.com

www.splunk.com

yaacomo.com

Technical documentation

github.com/rax-maas/blueflood/wiki

cratedb.com/docs

docs.splunk.com/Documentation/Splunk

Developer

Atos Convergence Creators

Rackspace

Crate

Splunk Inc.

Q2WEB GmbH

Initial release

2016

2013

2003

2009

Current release

1703

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

commercial

Limited free edition and free developer edition available

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

Java

Server operating systems

Linux

Linux
OS X

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

Linux
OS X
Solaris
Windows

Android
Linux
Windows

Data scheme

Schema and schema-less with LDAP views

predefined scheme

Flexible Schema (defined schema, partial schema, schema free)

yes

Typing

predefined data types such as float or date

optional

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

SQL

Support of SQL

yes, but no triggers and constraints, and PostgreSQL compatibility

Splunk Search Processing Language for search commands

yes

APIs and other access methods

LDAP

HTTP REST

ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

HTTP REST

JDBC
ODBC

Supported programming languages

All languages with LDAP bindings

.NET
Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
R
Ruby

community maintained client
Scala

community maintained client

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions (Javascript)

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

based on Cassandra

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on Cassandra

Configurable replication on table/partition-level

Multi-source replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency
Read-after-write consistency on record level

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

unique row identifiers can be used for implementing an optimistic concurrency control strategy

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

ACID

Concurrency

Support for concurrent manipulation of data

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

LDAP bind authentication

rights management via user accounts

Access rights for users and roles

fine grained access rights according to SQL-standard

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More resources

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