DBMS > Google Cloud Bigtable vs. Hazelcast vs. MySQL vs. Sphinx vs. Tarantool

System Properties Comparison Google Cloud Bigtable vs. Hazelcast vs. MySQL vs. Sphinx vs. Tarantool

Editorial information provided by DB-Engines

Name

Description

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

A widely adopted in-memory data grid

Widely used open source RDBMS

Open source search engine for searching in data from different sources, e.g. relational databases

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

Primary database model

Key-value store
Wide column store

Key-value store

Relational DBMS

Key/Value like access via memcached API

Search engine

Document store
Key-value store
Relational DBMS

Secondary database models

Document store

JSON support with IMDG 3.12

Document store
Spatial DBMS

Spatial DBMS

with Tarantool/GIS extension

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

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

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

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

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

Website

cloud.google.com/bigtable

Technical documentation

cloud.google.com/bigtable/docs

hazelcast.org/imdg/docs

dev.mysql.com/doc

sphinxsearch.com/docs

www.tarantool.io/en/doc

Developer

Google

Hazelcast

Oracle

since 2010, originally MySQL AB, then Sun

Sphinx Technologies Inc.

Initial release

2015

2008

1995

2001

2008

Current release

5.3.6, November 2023

8.4.0, April 2024

3.5.1, February 2023

2.10.0, May 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

GPL version 2, commercial licence available

Open Source

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

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C and C++

C++

C and C++

Server operating systems

hosted

All OS with a Java VM

FreeBSD
Linux
OS X
Solaris
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

BSD
Linux
macOS

Data scheme

schema-free

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

the object must implement a serialization strategy

yes

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

SQL-like query language (SphinxQL)

Full-featured ANSI SQL support

APIs and other access methods

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

JCache
JPA
Memcached protocol
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

Proprietary protocol

Open binary protocol

Supported programming languages

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

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

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

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

yes

proprietary syntax

Lua, C and SQL stored procedures

Triggers

yes

Events

yes

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

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

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.

Replication methods

Methods for redundantly storing data on multiple nodes

Internal replication in Colossus, and regional replication between two clusters in different zones

yes

Replicated Map

Multi-source replication
Source-replica replication

none

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 (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate 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

not for MyISAM storage engine

yes

Transaction concepts

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

Atomic single-row operations

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

ACID

not for MyISAM storage engine

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

table locks or row locks depending on storage engine

yes

yes, cooperative multitasking

Durability

Support for making data persistent

yes

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

yes, write ahead logging

In-memory capabilities

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

yes

yes, full featured in-memory storage engine with persistence

User concepts

Access control

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Role-based access control

Users with fine-grained authorization concept

no user groups or 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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