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DBMS > Google Cloud Spanner vs. Hawkular Metrics vs. IBM Db2 Event Store vs. Sphinx vs. Splice Machine

System Properties Comparison Google Cloud Spanner vs. Hawkular Metrics vs. IBM Db2 Event Store vs. Sphinx vs. Splice Machine

Editorial information provided by DB-Engines
NameGoogle Cloud Spanner  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionA 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.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Distributed Event Store optimized for Internet of Things use casesOpen source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSTime Series DBMSEvent Store
Time Series DBMS
Search engineRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.84
Rank#100  Overall
#51  Relational DBMS
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score0.27
Rank#309  Overall
#2  Event Stores
#28  Time Series DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitecloud.google.com/­spannerwww.hawkular.orgwww.ibm.com/­products/­db2-event-storesphinxsearch.comsplicemachine.com
Technical documentationcloud.google.com/­spanner/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidewww.ibm.com/­docs/­en/­db2-event-storesphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperGoogleCommunity supported by Red HatIBMSphinx Technologies Inc.Splice Machine
Initial release20172014201720012014
Current release2.03.5.1, February 20233.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercial infofree developer edition availableOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++C++Java
Server operating systemshostedLinux
OS X
Windows
Linux infoLinux, macOS, Windows for the developer additionFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesyesnoyes
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.nonono
Secondary indexesyesnonoyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLyes infoQuery statements complying to ANSI 2011noyes infothrough the embedded Spark runtimeSQL-like query language (SphinxQL)yes
APIs and other access methodsgRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
HTTP RESTADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Go
Java
Python
Ruby
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnonoyesnoyes infoJava
Triggersnoyes infovia Hawkular Alertingnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication with 3 replicas for regional instances.selectable replication factor infobased on CassandraActive-active shard replicationnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud DataflownononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoStrict serializable isolationnononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesNo - written data is immutableyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nofine grained access rights according to SQL-standardnoAccess rights for users, groups and roles according to SQL-standard

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More resources
Google Cloud SpannerHawkular MetricsIBM Db2 Event StoreSphinxSplice Machine
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