DBMS > EJDB vs. Manticore Search vs. Tarantool vs. Tigris

System Properties Comparison EJDB vs. Manticore Search vs. Tarantool vs. Tigris

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Editorial information provided by DB-Engines

Name

Description

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Multi-storage database for search, including full-text search.

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

A horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructure

Primary database model

Document store

Search engine

Document store
Key-value store
Relational DBMS

Document store
Key-value store
Search engine
Time Series DBMS

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Spatial DBMS

with Tarantool/GIS extension

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

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	0.22
Rank	#312	Overall
	#21	Search engines

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

Score	0.02
Rank	#369	Overall
	#51	Document stores
	#55	Key-value stores
	#24	Search engines
	#38	Time Series DBMS

Website

github.com/Softmotions/ejdb

manticoresearch.com

www.tarantool.io

www.tigrisdata.com

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

manual.manticoresearch.com

www.tarantool.io/en/doc

www.tigrisdata.com/docs

Developer

Softmotions

Manticore Software

Tigris Data, Inc.

Initial release

2012

2017

2008

2022

Current release

6.0, February 2023

2.10.0, May 2022

License

Commercial or Open Source

Open Source

GPLv2

Open Source

GPL version 2

Open Source

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

Open Source

Apache Version 2.0

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 C++

Server operating systems

server-less

FreeBSD
Linux
macOS
Windows

BSD
Linux
macOS

Linux
macOS
Windows

Data scheme

schema-free

Fixed schema

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

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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

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.

Can index from XML

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

SQL-like query language

Full-featured ANSI SQL support

APIs and other access methods

in-process shared library

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

Open binary protocol

CLI Client
gRPC
RESTful HTTP API

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

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

Go
Java
JavaScript (Node.js)

Server-side scripts

Stored procedures

user defined functions

Lua, C and SQL stored procedures

Triggers

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

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Synchronous replication based on Galera library

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

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

yes

isolated transactions for atomic changes and binary logging for safe writes

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

yes, cooperative multitasking

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Manticore index.

yes, write ahead logging

yes, using FoundationDB

In-memory capabilities

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

yes, full featured in-memory storage engine with persistence

User concepts

Access control

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

Access rights for users and roles

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More resources

DB-Engines blog posts

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

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