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DBMS > etcd vs. Google Cloud Bigtable vs. Informix vs. Splice Machine

System Properties Comparison etcd vs. Google Cloud Bigtable vs. Informix vs. Splice Machine

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Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonInformix  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionA distributed reliable key-value storeGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things dataOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelKey-value storeKey-value store
Wide column store
Relational DBMS infoSince Version 12.10 support for JSON/BSON datatypes compatible with MongoDBRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMS infowith Informix TimeSeries Extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.03
Rank#54  Overall
#5  Key-value stores
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score17.12
Rank#34  Overall
#21  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteetcd.io
github.com/­etcd-io/­etcd
cloud.google.com/­bigtablewww.ibm.com/­products/­informixsplicemachine.com
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
cloud.google.com/­bigtable/­docsinformix.hcldoc.com
www.ibm.com/­support/­knowledgecenter/­SSGU8G/­welcomeIfxServers.html
splicemachine.com/­how-it-works
DeveloperGoogleIBM, HCL Technologies infoEffective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.Splice Machine
Initial release201519842014
Current release3.4, August 201914.10.FC5, November 20203.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial infofree developer edition availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC, C++ and JavaJava
Server operating systemsFreeBSD
Linux
Windows infoexperimental
hostedAIX
HP-UX
Linux
macOS
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or datenonoyes infoSince Version 12.10 support for JSON/BSON datatypesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nono
Secondary indexesnonoyesyes
SQL infoSupport of SQLnonoyesyes
APIs and other access methodsgRPC
JSON over HTTP
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
JSON API infoMongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnonoyesyes infoJava
Triggersyes, watching key changesnoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Internal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users with fine-grained authentication, authorization, and auditing controlsAccess rights for users, groups and roles according to SQL-standard

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More resources
etcdGoogle Cloud BigtableInformixSplice Machine
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