DBMS > Brytlyt vs. MarkLogic vs. RocksDB vs. Splunk vs. XTDB

System Properties Comparison Brytlyt vs. MarkLogic vs. RocksDB vs. Splunk vs. XTDB

Editorial information provided by DB-Engines

Name

Description

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

Operational and transactional Enterprise NoSQL database

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Analytics Platform for Big Data

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

Primary database model

Relational DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Key-value store

Search engine

Document store

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

Score	0.29
Rank	#288	Overall
	#131	Relational DBMS

Score	5.92
Rank	#58	Overall
	#10	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#6	Search engines

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	86.45
Rank	#14	Overall
	#2	Search engines

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

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

Technical documentation

docs.brytlyt.io

docs.marklogic.com

github.com/facebook/rocksdb/wiki

docs.splunk.com/Documentation/Splunk

www.xtdb.com/docs

Developer

Brytlyt

MarkLogic Corp.

Facebook, Inc.

Splunk Inc.

Juxt Ltd.

Initial release

2016

2001

2013

2003

2019

Current release

5.0, August 2023

11.0, December 2022

9.2.1, May 2024

1.19, September 2021

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

BSD

commercial

Limited free edition and free developer edition available

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++ and CUDA

C++

Clojure

Server operating systems

Linux
OS X
Windows

Linux

Linux
OS X
Solaris
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

Schema can be enforced

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

specific XML-type available, but no XML query functionality.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL92

Splunk Search Processing Language for search commands

limited SQL, making use of Apache Calcite

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

C++ API
Java API

HTTP REST

HTTP REST
JDBC

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

C
C++
Go
Java
Perl
Python
Ruby

C#
Java
JavaScript
PHP
Python
Ruby

Clojure
Java

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

yes

via XQuery or JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Multi-source replication

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

can act as a resource manager in an XA/JTA transaction

yes

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

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, with Range Indexes

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Role-based access control at the document and subdocument levels

Access rights for users and roles

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