DBMS > Badger vs. Blueflood vs. Google Cloud Spanner vs. MaxDB

System Properties Comparison Badger vs. Blueflood vs. Google Cloud Spanner vs. MaxDB

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Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

Scalable TimeSeries DBMS based on Cassandra

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.

A robust and reliable RDBMS optimized to run all major SAP solutions

Primary database model

Key-value store

Time Series DBMS

Relational DBMS

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

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	2.89
Rank	#103	Overall
	#52	Relational DBMS

Score	2.32
Rank	#112	Overall
	#55	Relational DBMS

Website

github.com/dgraph-io/badger

blueflood.io

cloud.google.com/spanner

maxdb.sap.com

Technical documentation

godoc.org/github.com/dgraph-io/badger

github.com/rax-maas/blueflood/wiki

cloud.google.com/spanner/docs

maxdb.sap.com/documentation

Developer

DGraph Labs

Rackspace

Google

SAP, acquired from Software AG (Adabas-D) in 1997

Initial release

2017

2013

2017

1984

Current release

7.9.10.12, February 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

commercial

Limited community edition free

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

Java

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
OS X

hosted

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

predefined scheme

yes

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

Query statements complying to ANSI 2011

yes

APIs and other access methods

HTTP REST

gRPC (using protocol buffers) API
JDBC

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

ADO.NET
JDBC
ODBC
WebDAV

Supported programming languages

Go
Java
JavaScript (Node.js)
Python

.Net
C#
Java
Perl
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

based on Cassandra

Multi-source replication with 3 replicas for regional instances.

Source-replica replication

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

none

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

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

yes

Transaction concepts

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

ACID

Strict serializable isolation

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.

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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