DBMS > EventStoreDB vs. KairosDB vs. Lovefield vs. Solr vs. Tarantool

System Properties Comparison EventStoreDB vs. KairosDB vs. Lovefield vs. Solr vs. Tarantool

Editorial information provided by DB-Engines

Name

Description

Industrial-strength, open-source database solution built from the ground up for event sourcing.

Distributed Time Series DBMS based on Cassandra or H2

Embeddable relational database for web apps written in pure JavaScript

A widely used distributed, scalable search engine based on Apache Lucene

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

Primary database model

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	1.10
Rank	#179	Overall
	#1	Event Stores

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Score	1.72
Rank	#144	Overall
	#25	Document stores
	#25	Key-value stores
	#66	Relational DBMS

Website

www.eventstore.com

github.com/kairosdb/kairosdb

google.github.io/lovefield

solr.apache.org

www.tarantool.io

Technical documentation

developers.eventstore.com

kairosdb.github.io

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

solr.apache.org/resources.html

www.tarantool.io/en/doc

Developer

Event Store Limited

Google

Apache Software Foundation

Initial release

2012

2013

2014

2006

2008

Current release

21.2, February 2021

1.2.2, November 2018

2.1.12, February 2017

9.6.0, April 2024

2.10.0, May 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

Apache Version 2

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

Java

C and C++

Server operating systems

Linux
Windows

Linux
OS X
Windows

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

tested with Chrome, Firefox, IE, Safari

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

BSD
Linux
macOS

Data scheme

schema-free

yes

Dynamic Fields enables on-the-fly addition of new fields

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

supports customizable data types and automatic typing

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

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

Solr Parallel SQL Interface

Full-featured ANSI SQL support

APIs and other access methods

Graphite protocol
HTTP REST
Telnet API

Java API
RESTful HTTP/JSON API

Open binary protocol

Supported programming languages

Java
JavaScript

Node.js
PHP
Python

JavaScript

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

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

Server-side scripts

Stored procedures

Java plugins

Lua, C and SQL stored procedures

Triggers

Using read-only observers

yes

User configurable commands triggered on index changes

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

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

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

selectable replication factor

based on Cassandra

none

yes

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

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

optimistic locking

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

yes, full featured in-memory storage engine with persistence

User concepts

Access control

simple password-based access control

yes

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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