DBMS > Google Cloud Bigtable vs. Graphite vs. PouchDB vs. RocksDB vs. SAP Adaptive Server

System Properties Comparison Google Cloud Bigtable vs. Graphite vs. PouchDB vs. RocksDB vs. SAP Adaptive Server

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.

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

JavaScript DBMS with an API inspired by CouchDB

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

The SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMS

Primary database model

Key-value store
Wide column store

Secondary database models

Spatial DBMS

with Boeing's Spatial Query Server

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

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	4.83
Rank	#67	Overall
	#4	Time Series DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	35.09
Rank	#25	Overall
	#17	Relational DBMS

Website

cloud.google.com/bigtable

github.com/graphite-project/graphite-web

pouchdb.com

rocksdb.org

www.sap.com/products/technology-platform/sybase-ase.html

Technical documentation

cloud.google.com/bigtable/docs

graphite.readthedocs.io

pouchdb.com/guides

github.com/facebook/rocksdb/wiki

help.sap.com/docs/SAP_ASE

Developer

Google

Chris Davis

Apache Software Foundation

Facebook, Inc.

SAP, Sybase

Initial release

2015

2006

2012

2013

1987

Current release

7.1.1, June 2019

9.2.1, May 2024

16.0

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

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

Python

JavaScript

C++

C and C++

Server operating systems

hosted

Linux
Unix

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

Linux

AIX
HP-UX
Linux
Solaris
Unix
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

Numeric data only

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.

Secondary indexes

yes

via views

yes

SQL

Support of SQL

yes

APIs and other access methods

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

HTTP API
Sockets

HTTP REST

only for PouchDB Server
JavaScript API

C++ API
Java API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

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

JavaScript (Node.js)
Python

JavaScript

C
C++
Go
Java
Perl
Python
Ruby

C
C++
Cobol
Java
Java
Perl
PHP
Python

Server-side scripts

Stored procedures

View functions in JavaScript

Java and Transact-SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

with a proxy-based framework, named couchdb-lounge

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

yes

Multi-source replication
Source-replica replication

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)

none

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic single-row operations

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

locking

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

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)

fine grained access rights according to SQL-standard

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