DBMS > ArcadeDB vs. CrateDB vs. Riak TS vs. Splunk

System Properties Comparison ArcadeDB vs. CrateDB vs. Riak TS vs. Splunk

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Editorial information provided by DB-Engines

Name

Description

Fast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewritten

Distributed Database based on Lucene

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Analytics Platform for Big Data

Primary database model

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Time Series DBMS

Search engine

Secondary database models

Relational DBMS

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

Score	0.02
Rank	#374	Overall
	#52	Document stores
	#38	Graph DBMS
	#56	Key-value stores
	#38	Time Series DBMS

Score	0.69
Rank	#226	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#11	Vector DBMS

Score	0.17
Rank	#318	Overall
	#27	Time Series DBMS

Score	93.02
Rank	#13	Overall
	#2	Search engines

Website

arcadedb.com

cratedb.com

www.splunk.com

Technical documentation

docs.arcadedb.com

cratedb.com/docs

www.tiot.jp/riak-docs/riak/ts/latest

docs.splunk.com/Documentation/Splunk

Developer

Arcade Data

Crate

Open Source, formerly Basho Technologies

Splunk Inc.

Initial release

2021

2013

2015

2003

Current release

September 2021

5.8.1, August 2024

3.0.0, September 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

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

Java

Erlang

Server operating systems

All OS with a Java VM

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

Linux
OS X

Linux
OS X
Solaris
Windows

Data scheme

schema-free

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

schema-free

yes

Typing

predefined data types such as float or date

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

restricted

yes

SQL

Support of SQL

SQL-like query language, no joins

yes, but no triggers and constraints, and PostgreSQL compatibility

yes, limited

Splunk Search Processing Language for search commands

APIs and other access methods

JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin

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

HTTP API
Native Erlang Interface

HTTP REST

Supported programming languages

Java

.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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions (Javascript)

Erlang

yes

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Configurable replication on table/partition-level

selectable replication factor

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Read-after-write consistency on record level

Eventual Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

links between datasets can be stored

Transaction concepts

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

ACID

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

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.

User concepts

Access control

rights management via user accounts

Access rights for users and roles

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More resources

DB-Engines blog posts

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