DBMS > Google Cloud Bigtable vs. Sadas Engine vs. SWC-DB vs. TigerGraph vs. XTDB

System Properties Comparison Google Cloud Bigtable vs. Sadas Engine vs. SWC-DB vs. TigerGraph vs. XTDB

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.

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

A high performance, scalable Wide Column DBMS

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Key-value store
Wide column store

Secondary database models

Time Series DBMS

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	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

cloud.google.com/bigtable

www.sadasengine.com

github.com/kashirin-alex/swc-db
www.swcdb.org

www.tigergraph.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

cloud.google.com/bigtable/docs

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

docs.tigergraph.com

www.xtdb.com/docs

Developer

Google

SADAS s.r.l.

Alex Kashirin

Juxt Ltd.

Initial release

2015

2006

2020

2017

2019

Current release

8.0

0.5, April 2021

1.19, September 2021

License

Commercial or Open Source

commercial

free trial version available

Open Source

GPL V3

commercial

Open Source

MIT License

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++

Clojure

Server operating systems

hosted

AIX
Linux
Windows

Linux

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

SQL-like query language (GSQL)

limited SQL, making use of Apache Calcite

APIs and other access methods

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

JDBC
ODBC
Proprietary protocol

Proprietary protocol
Thrift

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

HTTP REST
JDBC

Supported programming languages

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

.Net
C
C#
C++
Groovy
Java
PHP
Python

C++

C++
Java

Clojure
Java

Server-side scripts

Stored procedures

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

yes, each node contains all data

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

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

Atomic single-row operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

yes

managed by 'Learn by Usage'

User concepts

Access control

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

Access rights for users, groups and roles according to SQL-standard

Role-based access control

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