DBMS > Google Cloud Bigtable vs. SingleStore vs. Transwarp StellarDB vs. XTDB

System Properties Comparison Google Cloud Bigtable vs. SingleStore vs. Transwarp StellarDB vs. XTDB

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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.

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

A distributed graph DBMS built for enterprise-level graph applications

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

Primary database model

Key-value store
Wide column store

Relational DBMS

Graph DBMS

Document store

Secondary database models

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

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

Score	2.97
Rank	#92	Overall
	#15	Key-value stores
	#8	Wide column stores

Score	4.02
Rank	#74	Overall
	#39	Relational DBMS

Score	0.00
Rank	#385	Overall
	#40	Graph DBMS

Score	0.13
Rank	#330	Overall
	#45	Document stores

Website

cloud.google.com/bigtable

www.singlestore.com

www.transwarp.cn/en/product/stellardb

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

Technical documentation

cloud.google.com/bigtable/docs

docs.singlestore.com

www.xtdb.com/docs

Developer

Google

SingleStore Inc.

Transwarp

Juxt Ltd.

Initial release

2015

2013

2019

Current release

8.5, January 2024

1.19, September 2021

License

Commercial or Open Source

commercial

free developer edition available

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++, Go

Clojure

Server operating systems

hosted

Linux

64 bit version required

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

Data scheme

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

but no triggers and foreign keys

SQL-like query language

limited SQL, making use of Apache Calcite

APIs and other access methods

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

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

OpenCypher

HTTP REST
JDBC

Supported programming languages

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

Bash
C
C#
Java
JavaScript (Node.js)
Python

Clojure
Java

Server-side scripts

Stored procedures

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

hash partitioning

horizontal partitioning

none

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

stores two copies of each physical data partition on two separate nodes

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

can define user-defined aggregate functions for map-reduce-style calculations

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

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

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.

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

User concepts

Access control

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

Fine grained access control via users, groups and roles

yes

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More resources

DB-Engines blog posts

Turbocharge Your Application Development Using WebAssembly With SingleStoreDB
17 October 2022, Akmal Chaudhri, SingleStore (sponsor)

Cloud-Based Analytics With SingleStoreDB
9 June 2022, Akmal Chaudhri, SingleStore (sponsor)

SingleStore: The Increasing Momentum of Multi-Model Database Systems
14 February 2022, Akmal Chaudhri, SingleStore (sponsor)

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Recent citations in the news

Google Cloud adds graph processing to Spanner, SQL support to Bigtable
1 August 2024, InfoWorld

Google introduces Bigtable SQL access and Spanner's new AI-ready features
1 August 2024, ZDNet

Google's AI-First Strategy Brings Vector Support To Cloud Databases
1 March 2024, Forbes

Google Cloud expands its database portfolio with new AI capabilities
1 August 2024, TechCrunch

Google Cloud Adds GenAI, Core Enhancements Across Data Platform
1 August 2024, The New Stack

provided by Google News

SingleStore Partners With Snowflake to Help Users Build Faster, More Efficient Real Time AI Applications
19 September 2024, businesswire.com

SingleStore CEO sees little future for purpose-built vector databases
24 January 2024, VentureBeat

Achieve near real-time analytics on Amazon DynamoDB with SingleStore
16 September 2024, AWS Blog

Building a Modern Database: Nikita Shamgunov on Postgres and Beyond
18 April 2024, Madrona Venture Group

SingleStore: We do vectors and you don’t need knowledge graphs
22 July 2024, Blocks & Files

provided by Google News

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