DBMS > Firebird vs. Hazelcast vs. Manticore Search vs. RocksDB vs. Sqrrl

System Properties Comparison Firebird vs. Hazelcast vs. Manticore Search vs. RocksDB vs. Sqrrl

Editorial information provided by DB-Engines

Name

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.

Description

Firebird is an open source RDBMS forked from Borland's InterBase

A widely adopted in-memory data grid

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

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

Adaptable, secure NoSQL built on Apache Accumulo

Primary database model

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Document store

JSON support with IMDG 3.12

Time Series DBMS

using the Manticore Columnar Library

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

Score	20.82
Rank	#30	Overall
	#18	Relational DBMS

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	0.22
Rank	#312	Overall
	#21	Search engines

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

Website

sqrrl.com

Technical documentation

www.firebirdsql.org/en/reference-manuals

hazelcast.org/imdg/docs

manual.manticoresearch.com

github.com/facebook/rocksdb/wiki

Developer

Firebird Foundation

Hazelcast

Manticore Software

Facebook, Inc.

Amazon

originally Sqrrl Data, Inc.

Initial release

2000

As fork of Borland's InterBase

2008

2017

2013

2012

Current release

5.0.0, January 2024

5.3.6, November 2023

6.0, February 2023

8.11.4, April 2024

License

Commercial or Open Source

Open Source

Initial Developer's Public License

Open Source

Apache Version 2; commercial licenses available

Open Source

GPL version 2

Open Source

BSD

commercial

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 and C++

Java

C++

Java

Server operating systems

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

All OS with a Java VM

FreeBSD
Linux
macOS
Windows

Linux

Data scheme

yes

schema-free

Fixed schema

schema-free

Typing

predefined data types such as float or date

yes

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

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

the object must implement a serialization strategy

Can index from XML

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

JCache
JPA
Memcached protocol
RESTful HTTP API

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

C++ API
Java API

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

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

C
C++
Go
Java
Perl
Python
Ruby

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

Server-side scripts

Stored procedures

PSQL

yes

Event Listeners, Executor Services

user defined functions

Triggers

yes

Events

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

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

horizontal partitioning

Sharding

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Replicated Map

Synchronous replication based on Galera library

yes

selectable replication factor

making use of Hadoop

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

one or two-phase-commit; repeatable reads; read commited

yes

isolated transactions for atomic changes and binary logging for safe writes

yes

Atomic updates per row, document, or graph entity

Concurrency

Support for concurrent manipulation of data

yes

Features a multi-generational MVCC architecture, readers do not block writers

yes

Durability

Support for making data persistent

yes

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

yes

In-memory capabilities

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

yes

User concepts

Access control

Users with fine-grained authorization concept

Role-based access control

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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