DBMS > Apache Druid vs. Lovefield vs. Splunk vs. Tarantool

System Properties Comparison Apache Druid vs. Lovefield vs. Splunk vs. Tarantool

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Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Embeddable relational database for web apps written in pure JavaScript

Analytics Platform for Big Data

In-memory computing platform with a flexible data schema for efficiently building high-performance applications

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Search engine

Document store
Key-value store
Relational DBMS

Secondary database models

Spatial DBMS

with Tarantool/GIS extension

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

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	89.10
Rank	#14	Overall
	#2	Search engines

Score	1.67
Rank	#143	Overall
	#25	Document stores
	#25	Key-value stores
	#65	Relational DBMS

Website

druid.apache.org

google.github.io/lovefield

www.splunk.com

www.tarantool.io

Technical documentation

druid.apache.org/docs/latest/design

github.com/google/lovefield/blob/master/docs/spec_index.md

docs.splunk.com/Documentation/Splunk

www.tarantool.io/en/doc

Developer

Apache Software Foundation and contributors

Google

Splunk Inc.

Initial release

2012

2014

2003

2008

Current release

29.0.1, April 2024

2.1.12, February 2017

2.10.0, May 2022

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache 2.0

commercial

Limited free edition and free developer edition available

Open Source

BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise

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

JavaScript

C and C++

Server operating systems

Linux
OS X
Unix

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
OS X
Solaris
Windows

BSD
Linux
macOS

Data scheme

yes

schema-less columns are supported

yes

Flexible data schema: relational definition for tables with ability to store json-like documents in columns

Typing

predefined data types such as float or date

yes

string, double, decimal, uuid, integer, blob, boolean, datetime

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

SQL for querying

SQL-like query language

via JavaScript builder pattern

Splunk Search Processing Language for search commands

Full-featured ANSI SQL support

APIs and other access methods

JDBC
RESTful HTTP/JSON API

HTTP REST

Open binary protocol

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

JavaScript

C#
Java
JavaScript
PHP
Python
Ruby

C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust

Server-side scripts

Stored procedures

yes

Lua, C and SQL stored procedures

Triggers

Using read-only observers

yes

yes, before/after data modification events, on replication events, client session events

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

Sharding

Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

none

Multi-source replication

Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)

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

Casual consistency across sharding partitions
Eventual consistency within replicaset partition

when using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition

when using Raft

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

ACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions

Concurrency

Support for concurrent manipulation of data

yes

yes, cooperative multitasking

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

yes, write ahead logging

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

yes, full featured in-memory storage engine with persistence

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Access rights for users and roles

Access Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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More resources

DB-Engines blog posts

Enterprise Search Engines almost double their popularity in the last 12 months
2 July 2014, Paul Andlinger

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Data processing speed and reliability: in-memory synchronous replication
9 November 2021, Vladimir Perepelytsya, Tarantool (sponsor)

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