DBMS > Google Cloud Bigtable vs. Graph Engine vs. Linter vs. Machbase vs. Sqrrl

System Properties Comparison Google Cloud Bigtable vs. Graph Engine vs. Linter vs. Machbase 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

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 distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

RDBMS for high security requirements

TimeSeries DBMS for AIoT and BigData

Adaptable, secure NoSQL built on Apache Accumulo

Primary database model

Key-value store
Wide column store

Graph DBMS
Key-value store

Relational DBMS

Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Spatial DBMS

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

Score	4.26
Rank	#86	Overall
	#14	Key-value stores
	#6	Wide column stores

Score	0.91
Rank	#184	Overall
	#16	Graph DBMS
	#30	Key-value stores

Score	0.11
Rank	#309	Overall
	#142	Relational DBMS

Score	0.01
Rank	#348	Overall
	#32	Time Series DBMS

Website

cloud.google.com/bigtable

www.graphengine.io

linter.ru/en

www.machbase.com

sqrrl.com

Technical documentation

cloud.google.com/bigtable/docs

www.graphengine.io/docs/manual

endoc.machbase.com

Developer

Google

Microsoft

relex.ru/en

Machbase

Amazon

originally Sqrrl Data, Inc.

Initial release

2015

2010

1990

2013

2012

Current release

V6.5, August 2021

License

Commercial or Open Source

commercial

Open Source

MIT License

commercial

free test version available

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

.NET and C

C and C++

Java

Server operating systems

hosted

.NET

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

Linux
Windows

Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

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

RESTful HTTP API

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

HTTP REST
JDBC
ODBC

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

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

C#
C++
F#
Visual Basic

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

C
C#
C++
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

Actionscript
C

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

Server-side scripts

Stored procedures

yes

proprietary syntax with the possibility to convert from PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

none

Sharding

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

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

Source-replica replication

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

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

Atomic single-row operations

ACID

Atomic updates per row, document, or graph entity

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

In-memory capabilities

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

yes

volatile and lookup table

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

simple password-based access control

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

More information provided by the system vendor

Specific characteristics

Machbase is an extremely fast time series database which processes large volumes...
» more

Competitive advantages

Fastest Database for IIoT, Independently verified, on Industry Standard Benchmarks....
» more

Typical application scenarios

Distributed Query In Machbase Cluster Edition, a broker node, which is responsible...
» more

Key customers

Machbase has over 50 customers, including Samsung, POSCO, and Hyundai.
» more

Market metrics

Real-time data processing Real-time index creation Optimized DBMS for processing...
» more

Licensing and pricing models

Machbase provide several product editions, including: Intelligent Edge Device, Fog...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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