DBMS > Google Cloud Spanner vs. Memcached vs. RocksDB vs. SQream DB

System Properties Comparison Google Cloud Spanner vs. Memcached vs. RocksDB vs. SQream DB

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Editorial information provided by DB-Engines

Name

Description

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

In-memory key-value store, originally intended for caching

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

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Relational DBMS

Key-value store

Relational DBMS

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

Score	2.89
Rank	#105	Overall
	#53	Relational DBMS

Score	20.74
Rank	#32	Overall
	#4	Key-value stores

Score	4.00
Rank	#84	Overall
	#11	Key-value stores

Score	0.73
Rank	#228	Overall
	#105	Relational DBMS

Website

cloud.google.com/spanner

www.memcached.org

rocksdb.org

sqream.com

Technical documentation

cloud.google.com/spanner/docs

github.com/memcached/memcached/wiki

github.com/facebook/rocksdb/wiki

docs.sqream.com

Developer

Google

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Facebook, Inc.

SQream Technologies

Initial release

2017

2003

2013

2017

Current release

1.6.25, March 2024

8.11.4, April 2024

2022.1.6, December 2022

License

Commercial or Open Source

commercial

Open Source

BSD license

Open Source

BSD

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

C++, CUDA, Haskell, Java, Scala

Server operating systems

hosted

FreeBSD
Linux
OS X
Unix
Windows

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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.

Secondary indexes

yes

SQL

Support of SQL

yes

Query statements complying to ANSI 2011

yes

APIs and other access methods

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

Proprietary protocol

C++ API
Java API

.Net
JDBC
ODBC

Supported programming languages

Go
Java
JavaScript (Node.js)
Python

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

C
C++
Go
Java
Perl
Python
Ruby

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions in Python

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication with 3 replicas for regional instances.

none

Repcached, a Memcached patch, provides this functionallity

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

Transaction concepts

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

ACID

Strict serializable isolation

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

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

yes

using SASL (Simple Authentication and Security Layer) protocol

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